A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves
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 axon...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-03-01
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| Series: | Frontiers in Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2023.1072779/full |
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| author | Abida Sanjana Shemonti Emanuele Plebani Natalia P. Biscola Deborah M. Jaffey Leif A. Havton Leif A. Havton Leif A. Havton Janet R. Keast Alex Pothen M. Murat Dundar Terry L. Powley Bartek Rajwa |
| author_facet | Abida Sanjana Shemonti Emanuele Plebani Natalia P. Biscola Deborah M. Jaffey Leif A. Havton Leif A. Havton Leif A. Havton Janet R. Keast Alex Pothen M. Murat Dundar Terry L. Powley Bartek Rajwa |
| author_sort | Abida Sanjana Shemonti |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-10T05:13:13Z |
| format | Article |
| id | doaj.art-ec13564424114d20b07151bd0525e319 |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-04-10T05:13:13Z |
| publishDate | 2023-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-ec13564424114d20b07151bd0525e3192023-03-09T05:59:52ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2023-03-011710.3389/fnins.2023.10727791072779A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nervesAbida Sanjana Shemonti0Emanuele Plebani1Natalia P. Biscola2Deborah M. Jaffey3Leif A. Havton4Leif A. Havton5Leif A. Havton6Janet R. Keast7Alex Pothen8M. Murat Dundar9Terry L. Powley10Bartek Rajwa11Department of Computer Science, Purdue University, West Lafayette, IN, United StatesDepartment of Computer & Information Sciences, Indiana University - Purdue University Indianapolis, Indianapolis, IN, United StatesDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Psychological Sciences, Purdue University, West Lafayette, IN, United StatesDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesJames J. Peters Department of Veterans Affairs Medical Center, Bronx, NY, United StatesDepartment of Anatomy and Physiology, University of Melbourne, Melbourne, VIC, AustraliaDepartment of Computer Science, Purdue University, West Lafayette, IN, United StatesDepartment of Computer & Information Sciences, Indiana University - Purdue University Indianapolis, Indianapolis, IN, United StatesDepartment of Psychological Sciences, Purdue University, West Lafayette, IN, United StatesBindley Bioscience Center, Purdue University, West Lafayette, IN, United StatesA 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.https://www.frontiersin.org/articles/10.3389/fnins.2023.1072779/fullperipheral nervous systemneuroanatomyneuromodulationspatial point processoptimal transport problemSinkhorn distance |
| spellingShingle | Abida Sanjana Shemonti Emanuele Plebani Natalia P. Biscola Deborah M. Jaffey Leif A. Havton Leif A. Havton Leif A. Havton Janet R. Keast Alex Pothen M. Murat Dundar Terry L. Powley Bartek Rajwa A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves Frontiers in Neuroscience peripheral nervous system neuroanatomy neuromodulation spatial point process optimal transport problem Sinkhorn distance |
| title | A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves |
| title_full | A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves |
| title_fullStr | A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves |
| title_full_unstemmed | A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves |
| title_short | A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves |
| title_sort | novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves |
| topic | peripheral nervous system neuroanatomy neuromodulation spatial point process optimal transport problem Sinkhorn distance |
| url | https://www.frontiersin.org/articles/10.3389/fnins.2023.1072779/full |
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