Quantitative, multimodal cell and fiber mapping in full primate brain sections

Poster No:

2114 

Submission Type:

Abstract Submission 

Authors:

Roxana Kooijmans1,2, Markus Axer2, Eric Upschulte2, Timo Dickscheid2, Martin Schober2, David Gräßel2, Philipp Schlömer2, Karl Zilles2, Pieter Roelfsema1, Katrin Amunts2

Institutions:

1Netherlands Institute for Neuroscience, Amsterdam, Noord Holland, 2Institute for Neuroscience and Medicine (INM-1), FZ-Jülich, Jülich, Nordrhein-Westfalen

First Author:

Roxana Kooijmans, PhD  
Netherlands Institute for Neuroscience|Institute for Neuroscience and Medicine (INM-1), FZ-Jülich
Amsterdam, Noord Holland|Jülich, Nordrhein-Westfalen

Co-Author(s):

Markus Axer  
Institute for Neuroscience and Medicine (INM-1), FZ-Jülich
Jülich, Nordrhein-Westfalen
Eric Upschulte  
Institute for Neuroscience and Medicine (INM-1), FZ-Jülich
Jülich, Nordrhein-Westfalen
Timo Dickscheid  
Institute for Neuroscience and Medicine (INM-1), FZ-Jülich
Jülich, Nordrhein-Westfalen
Martin Schober  
Institute for Neuroscience and Medicine (INM-1), FZ-Jülich
Jülich, Nordrhein-Westfalen
David Gräßel  
Institute for Neuroscience and Medicine (INM-1), FZ-Jülich
Jülich, Nordrhein-Westfalen
Philipp Schlömer  
Institute for Neuroscience and Medicine (INM-1), FZ-Jülich
Jülich, Nordrhein-Westfalen
Karl Zilles  
Institute for Neuroscience and Medicine (INM-1), FZ-Jülich
Jülich, Nordrhein-Westfalen
Pieter Roelfsema, PhD  
Netherlands Institute for Neuroscience
Amsterdam, Noord Holland
Katrin Amunts  
Institute for Neuroscience and Medicine (INM-1), FZ-Jülich
Jülich, Nordrhein-Westfalen

Introduction:

Detailed multi-modal architecture information is the basis for understanding function, dysfunction, and potential treatment of the brain. Mouse models have led the establishment of new molecular markers and have engendered a rise in understanding cell-specific function. Information based on such markers in the human brain is highly fragmented, and major parts are missing. While cell types often exhibit homology across species, the size and organizational complexity of the human brain make direct inference of function from mouse data problematic. There are multiple efforts to generate complete and consistent maps for various species, but none addresses (quantitative) protein expression in combination with direct imaging of fiber distribution patterns.
We aim to bridge this gap by using our newly developed method to integrate multi-channel, cell-type specific immunohistochemistry with polarized light imaging (3D-PLI), to map protein expression, as well as fiber architecture in 3D-space, in the same, full, primate brain sections.

Methods:

We imaged fiber tracts in 60µm-thick, unstained, primate brain sections at 1.3 µm pixel size in-plane, using polarization microscopy [1]. Based on these measurements, regional fiber orientation maps were determined by means of big data analysis utilizing high-performance computing (JURECA supercomputer, JSC, Forschungszentrum Jülich). Subsequently, we unmounted the tissue, and use immunohistochemistry to specifically label cells expressing calcium binding proteins parvalbumin, calbindin and calretinin, in the same section [2]. We remounted the sections, and acquired 1µm resolution, full color images with fast brightfield scanning. Subsequently, we segmented the stained cell bodies using machine learning, and separated the different populations based on color, to describe cellular distributions with high accuracy. The two data sets were co-aligned section-wise, using non-linear registration to render multi-modal cell and fiber analysis possible.

Results:

Based on the described methods, we were able to generate and visualize both fiber architecture and protein distributions in the same primate brain sections, at micrometer resolution (Figure 1). In addition, we developed a method to segment cell bodies in the immunohistochemistry-based images using machine learning, separate the data into multiple channels using the colored staining, and objectively quantify cell distribution the along cortical depth (Figure 2).
Supporting Image: OHBM_1.png
Supporting Image: OHBM_2.png
 

Conclusions:

We show that we can specifically, reliably, and quantitatively map subsets of cells based on their protein expression with respect to cortical layers, and deliver information about the primate brain architecture which is highly complementary to existing data. This approach enables the visualization, segmentation, classification, and quantification of distinct cell populations, as defined by protein expression, in the context of the local and global fiber architecture, within the same section. Ultimately, we aim to obtain a complete, consistent, and multi-modal map of the human brain, to be integrated into the atlas of the Human Brain Project, and made available to the international research community.

Neuroanatomy, Physiology, Metabolism and Neurotransmission:

Cortical Anatomy and Brain Mapping
Cortical Cyto- and Myeloarchitecture

Neuroinformatics and Data Sharing:

Brain Atlases 2

Novel Imaging Acquisition Methods:

Multi-Modal Imaging 1
Polarized light imaging (PLI)

Keywords:

Atlasing
Cellular
Cortex
Machine Learning
NORMAL HUMAN
Tractography

1|2Indicates the priority used for review

My abstract is being submitted as a Software Demonstration.

No

Please indicate below if your study was a "resting state" or "task-activation” study.

Other

Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Healthy subjects

Was any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.

Not applicable

Was any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

Not applicable

Please indicate which methods were used in your research:

Postmortem anatomy

Provide references using author date format

[1] Axer, M., Gräßel, D., Kleiner, M., Dammers, J., Dickscheid, T., Reckfort, J., Hutz, T., Eiben, B., Pietrzyk, U., Zilles, K., Amunts, K. (2011), ‘High-resolution fiber tract reconstruction in the human brain by means of three-dimensional polarized light imaging’. Front Neuroinform, 5, 34.
[2] Kooijmans, R.N., Axer, M., Schober, M., Gräßel, D., Schlömer, P., Zilles, K., Roelfsema, P.R., Amunts, K. (2019), ‘Multimodal cell and fiber mapping in full vervet brain sections’. Society for Neuroscience.

Acknowledgments: This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No.785907 (Human Brain Project, SGA2). We gratefully acknowledge the computing time granted through JARA-HPC on the supercomputer JURECA at Forschungszentrum Jülich (FZJ), Germany.