Exploring large-scale cortical organization in chimpanzees: probing myeloarchitecture with qMRI

Poster No:

1503 

Submission Type:

Abstract Submission 

Authors:

Ilona Lipp1, Evgeniya Kirilina1, Carsten Jäger1, Markus Morawski2, Anna Jauch1, Sofie Valk1, Kerrin Pine1, Luke Edwards1, Cornelius Eichner1, Tobias Gräßle3, Alfred Anwander1, Angela Friederici1, Roman Wittig4, Catherine Crockford4, Nikolaus Weiskopf1

Institutions:

1Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2Paul Flechsig Institute of Brain Research, University of Leipzig, Leipzig, Germany, 3Epidemiology of Highly Pathogenic Microorganisms, Robert Koch Institute, Beriln, Germany, 4Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

First Author:

Ilona Lipp  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany

Co-Author(s):

Evgeniya Kirilina  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Carsten Jäger  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Markus Morawski  
Paul Flechsig Institute of Brain Research, University of Leipzig
Leipzig, Germany
Anna Jauch  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Sofie Valk  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Kerrin Pine  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Luke Edwards  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Cornelius Eichner  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Tobias Gräßle  
Epidemiology of Highly Pathogenic Microorganisms, Robert Koch Institute
Beriln, Germany
Alfred Anwander  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Angela Friederici  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Roman Wittig  
Max Planck Institute for Evolutionary Anthropology
Leipzig, Germany
Catherine Crockford  
Max Planck Institute for Evolutionary Anthropology
Leipzig, Germany
Nikolaus Weiskopf  
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany

Introduction:

MRI-based comparative neuroscience provides unique insights into the evolution of the human brain [1,2]. Large-scale principles of information processing can be uncovered by studying the spatial dimensions of cortical organisation, the so-called cortical gradients [3,4]. These organisational principles are reflected in functional and structural connectivity of related cortical regions as well as in the similarity of their microstructure [5]. This principle, which was initially discovered using histology, can now also be investigated through microstructural profiles obtained from MRI at sub-mm-resolution [6]. To date, a complete understanding of the organization of the chimpanzee cortex, which are the closest living relatives to humans, is lacking. Ethical concerns have widely stopped in vivo MRI research and existing data are sparse. Here, we use post-mortem ultra-high resolution quantitative MRI data from brains of chimanzees, who died in the wild or in zoos from natural causes, to investigate the large-scale cortical organisation through myeloarchitecture.

Methods:

Brains were collected and formalin-fixed in phosphate buffered saline solution at pH 7.4 between 4 and 24 hours after death. The brains were embedded in Fomblin and scanned in a human 7T MRI scanner (Siemens Healthineers, Erlangen, Germany). Multi-parameter mapping [7] was performed on the whole brains at 300μm isotropic resolution (TR = 70ms, 12 equispaced echoes, TE = 3.63-41.7ms, flip angles: 18º, 82º, MT pulse: 3kHz offset, 800º, acquisition matrix: 448 x 392 x 288) to obtain maps of various myelin-sensitive quantitative MR parameters: longitudinal relaxation rate (R1), effective transverse relaxation rate (R2*) and magnetization transfer saturation (MTsat). MRI data from 8 chimpanzee brains (4 female, 4 male, 5 wild, 3 captive, age (mean±std): 32±20 years) were analysed. After segmenting white matter and pial surfaces using Freesurfer, equi-volume layering [8] was done across 5-95% of the cortical depth in 5% steps. The cortex was parcellated using the Bailey-Bonin chimpanzee atlas [2], yielding 38 nodes on each hemisphere. Microstructure profile covariance (MPC) for each parameter (R1, R2* and MTsat) was calculated by using partial correlation coefficients between the intracortical profiles of all nodes, controlling for the average profile across all nodes, followed by Fisher's z-transformation. The resulting three matrices were averaged across all brains. To identify cortical gradients, diffusion embedding was done on the averaged MPCs [9] using the software package Brainspace [10].

Results:

The quantitative parameters show a cortical distribution in line with previous work, with the strongest myelination in primary areas, such as motor and somatosensory cortex, and the lowest myelination in frontal cortices (Figure 1A). MPCs of the three investigated parameters display similar patterns (Figure 1B). The eigenvalues from diffusion embedding suggests only one principal gradient need be kept, explaining 40% of variance. This gradient mainly differentiates between two types of cortex, as evident from the gradient loadings. One pole of the gradient consists of unimodal cortex, such as primary motor and somatosensory cortex, while the other pole consists of transmodal cortices, such as cingulate and frontal cortex (Figure 1C).
Supporting Image: ohbm21fig_small.jpg
 

Conclusions:

A principle gradient of cortical organisation along a sensory-fugal axis has previously been shown in humans and macaques [3,6]. Here, we demonstrated the presence of a comparable principle cortical gradient for the first time (to our knowledge) in chimpanzees, using ultra-high resolution whole brain post-mortem quantitative MRI data. Our results emphasize the feasibility of microstructural profile covariance mapping with this ethical and sustainable brain sourcing approach. Extending our work will allow direct comparison of cortical organisation in various non-human primate species, gaining further insight into cortical evolution.

Neuroanatomy, Physiology, Metabolism and Neurotransmission:

Anatomy and Functional Systems
Cortical Anatomy and Brain Mapping 2
Cortical Cyto- and Myeloarchitecture 1

Novel Imaging Acquisition Methods:

Anatomical MRI

Keywords:

ANIMAL STUDIES
Cortex
Cortical Layers
Cross-Species Homologues
HIGH FIELD MR
Myelin

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:

Structural MRI
Postmortem anatomy

For human MRI, what field strength scanner do you use?

7T

Which processing packages did you use for your study?

SPM
Free Surfer

Provide references using author date format

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[2] Ardesch, D. J., Scholtens, L. H., Li, L., Preuss, T. M., Rilling, J. K., & van den Heuvel, M. P. (2019). Evolutionary expansion of connectivity between multimodal association areas in the human brain compared with chimpanzees. Proceedings of the National Academy of Sciences of the United States of America, 116(14), 7101–7106.

[3] Margulies, D. S., Ghosh, S. S., Goulas, A., Falkiewicz, M., Huntenburg, J. M., Langs, G., … Smallwood, J. (2016). Situating the default-mode network along a principal gradient of macroscale cortical organization. Proceedings of the National Academy of Sciences of the United States of America, 113(44), 12574–12579.

[4] Mesulam, M. M. (1998). From sensation to cognition. Brain, 121(6), 1013–1052.

[5] Cabezas-García, Á. M., Zikopoulos, B., & Barbas, H. (2019). The Structural Model: a theory linking connections, plasticity, pathology, development and evolution of the cerebral cortex. Brain Structure and Function, 224, 985–1008.

[6] Paquola, C., Vos De Wael, R., Wagstyl, K., Bethlehem, R. A. I., Hong, S. J., Seidlitz, J., … Bernhardt, B. C. (2019). Microstructural and Functional Gradients are Increasingly Dissociated in Transmodal Cortices. PLoS Biology, 17(5).

[7] Weiskopf, N., Suckling, J., Williams, G., Correia, M. M., & Inkster, B. (2013). Quantitative multi-parameter mapping of R1, PD, MT, and R2* at 3T: a multi-center validation. Frontiers in Neuroscience, 7, Article 95.

[8] Waehnert, M. D., Dinse, J., Weiss, M., Streicher, M. N., Waehnert, P., Geyer, S., … Bazin, P. L. (2014). Anatomically motivated modeling of cortical laminae. NeuroImage, 93, 210–220.

[9] Paquola, C., Bethlehem, R. A., Seidlitz, J., Wagstyl, K., Romero-Garcia, R., Whitaker, K. J., … Bullmore, E. T. (2019). Shifts in myeloarchitecture characterise adolescent development of cortical gradients. ELife, 8, 1–23.

[10] Vos de Wael, R., Benkarim, O., Paquola, C., Lariviere, S., Royer, J., Tavakol, S., … Bernhardt, B. C. (2020). BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets. Communications Biology, 3(1).