Precise registration of axonal morphologies obtained from sections to a common reference space

We present a strategy to register manually traced neuronal morphologies to a reference atlas, with the final goal to publish the aligned neurons in the EBRAINS knowledge-graph, visualize them in the interactive atlas viewer and compare them to other published neurons.

Our use case consists of a thalamo-cortical long-range projection neuron that is manually traced from 33 sagittal tissue sections of a mouse brain. We apply a three-step procedure:1. Manually select for each tissue section a corresponding slice from a reference atlas.2. Deform each tissue section such that its outline and anatomical features match that of the corresponding reference slice.3. For each section, apply the same deformation to the portion of the neuron that it intersects.

A trained neuroanatomist confirmed the correct thalamic and cortical positioning of the neuron. In terms of the alignment of the neuron with respect to cortical layers, we found up to 50% discrepancies. A procedure was developed to shift the cortical depth of the neuron and reduce the error to below 10%.

Content

Author and article information

Journal

Title: ScienceOpen Posters

Publisher: ScienceOpen

Publication date (Electronic preprint): 21 July 2023

Affiliations

[1 ] Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Department of Neuroinformatics, Nijmegen, The Netherlands;

[2 ] Department of Clinical Neurophysiology, Institute for Technical Medicine, University of Twente, Technical Medical Centre, Enschede, The Netherlands;

[3 ] Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany;

[4 ] Department of Anatomy and Neuroscience, School of Medicine, Autónoma de Madrid University, Madrid, Spain;

Author notes

[* ]Email: rembrandt.bakker@ 123456donders.ru.nl .

Author information

Maria Carla Piastra https://orcid.org/0000-0001-8339-0355

Rembrandt Bakker https://orcid.org/0000-0002-2942-2691

Maria Garcia-Amado https://orcid.org/0000-0001-6778-5680

Mario Rubio-Teves https://orcid.org/0000-0002-1405-9885

Francisco Clascá https://orcid.org/0000-0003-0718-1337

Paul Tiesinga https://orcid.org/0000-0003-4509-6870

Article

DOI: 10.14293/P2199-8442.1.SOP-.PJ4UFX.v1

SO-VID: 6f778149-0239-4ce0-adaa-dda4a33dd5c8

License:

This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

History

Date received : 21 July 2023

Funding

Funded by: funder-id http://dx.doi.org/10.13039/501100003246, Nederlandse Organisatie voor Wetenschappelijk Onderzoek;

Award ID: 80-91-318

Funded by: funder-id http://dx.doi.org/10.13039/100010661, Horizon 2020 Framework Programme;

Award ID: HBP SGA3 945539

Funded by: funder-id http://dx.doi.org/10.13039/501100004837, Ministerio de Ciencia e Innovación;

Award ID: PCI2019-111900-2

References

Bakker Rembrandt, Tiesinga Paul, Kötter Rolf. The Scalable Brain Atlas: Instant Web-Based Access to Public Brain Atlases and Related Content. Neuroinformatics. Vol. 13(3):353–366. 2015. Springer Science and Business Media LLC. [Cross Ref]
Klein S., Staring M., Murphy K., Viergever M.A., Pluim J.. elastix: A Toolbox for Intensity-Based Medical Image Registration. IEEE Transactions on Medical Imaging. Vol. 29(1):196–205. 2010. Institute of Electrical and Electronics Engineers (IEEE). [Cross Ref]
Puchades Maja A., Csucs Gergely, Ledergerber Debora, Leergaard Trygve B., Bjaalie Jan G.. Spatial registration of serial microscopic brain images to three-dimensional reference atlases with the QuickNII tool. PLOS ONE. Vol. 14(5)2019. Public Library of Science (PLoS). [Cross Ref]
Shamonin Denis. Fast parallel image registration on CPU and GPU for diagnostic classification of Alzheimer's disease. Frontiers in Neuroinformatics. Vol. 7:2013. Frontiers Media SA. [Cross Ref]
Tang Meng, Gorelick Lena, Veksler Olga, Boykov Yuri. GrabCut in One Cut. 2013 IEEE International Conference on Computer Vision. 2013. IEEE. [Cross Ref]

Comments

Comment on this article

[1] Bakker Rembrandt, Tiesinga Paul, Kötter Rolf. The Scalable Brain Atlas: Instant Web-Based Access to Public Brain Atlases and Related Content. Neuroinformatics. Vol. 13(3):353–366. 2015. Springer Science and Business Media LLC. [Cross Ref]

[2] Klein S., Staring M., Murphy K., Viergever M.A., Pluim J.. elastix: A Toolbox for Intensity-Based Medical Image Registration. IEEE Transactions on Medical Imaging. Vol. 29(1):196–205. 2010. Institute of Electrical and Electronics Engineers (IEEE). [Cross Ref]

[3] Puchades Maja A., Csucs Gergely, Ledergerber Debora, Leergaard Trygve B., Bjaalie Jan G.. Spatial registration of serial microscopic brain images to three-dimensional reference atlases with the QuickNII tool. PLOS ONE. Vol. 14(5)2019. Public Library of Science (PLoS). [Cross Ref]

[4] Shamonin Denis. Fast parallel image registration on CPU and GPU for diagnostic classification of Alzheimer's disease. Frontiers in Neuroinformatics. Vol. 7:2013. Frontiers Media SA. [Cross Ref]

[5] Tang Meng, Gorelick Lena, Veksler Olga, Boykov Yuri. GrabCut in One Cut. 2013 IEEE International Conference on Computer Vision. 2013. IEEE. [Cross Ref]