Cytoarchitecture and brain-wide connectivity reveal topographic organization of insula networks

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Abstract Submission 

Erika Raven¹, Claude Y. Lepage², Joey Charbonneau³, Jelle Veraart¹, Jeff Bennett³, Alan Evans², Jiangyang Zhang¹, Eliza Bliss-Moreau³

¹New York University School of Medicine, New York, NY, ²McGill Centre for Integrative Neuroscience (MCIN), Montreal, Quebec, ³California National Primate Research Center, Davis, CA

Erika Raven  
New York University School of Medicine
New York, NY

Claude Y. Lepage  
McGill Centre for Integrative Neuroscience (MCIN)
Montreal, Quebec

Joey Charbonneau  
California National Primate Research Center
Davis, CA

Jelle Veraart  
New York University School of Medicine
New York, NY

Jeff Bennett  
California National Primate Research Center
Davis, CA

Alan Evans  
McGill Centre for Integrative Neuroscience (MCIN)
Montreal, Quebec

Jiangyang Zhang  
New York University School of Medicine
New York, NY

Eliza Bliss-Moreau  
California National Primate Research Center
Davis, CA

One of the major challenges to carrying out in vivo neuroanatomical analyses is that regional cytoarchitectural variation is difficult to capture by MRI. As a result, parcellation of brain regions is often limited to a scale too coarse for the understanding of their functions. While this presents a challenge for many regions of the brain, the insula is comprised of distinct laminar cyto-archetypes that form the basis of highly integrative whole brain networks. These subregions have been linked to an astonishing number of functional roles, and may ultimately be targets for future development of interventions in physical and mental health ^1–4. In order to capture the heterogeneity of these subregions and networks, it is necessary to improve the specificity of neuroanatomical data and analyses using resolutions across disparate spatial scales and contrasting modalities from within the same subjects. We present our first integrated (Mic)ro to (Mac)ro Macaque brain dataset, here called MicMac (Fig. 1). MicMac is an extendable workflow, represented by a within-subject whole brain dataset that integrates aligned multi-parametric in vivo MRI, high resolution ex vivo MRI, and histology within a single, standardized template space. We then translate this workflow to perform a group level network analysis to identify network features in an in vivo cohort of n=16 middle to older aged macaques (7-20 years, 3M, 13F).

The MicMac dataset was obtained from a 10.3 year old healthy female rhesus macaque. In vivo MRI scans were performed on a Siemens 3T equipped with an 8-channel monkey head coil. Ex vivo MRI were conducted on a Bruker 7T using a 72mm volume coil. Both in vivo and ex vivo imaging protocols were harmonized, and optimized for experimental factors such as tissue fixation. Multi-shell diffusion MRI (dMRI) was acquired for structural connectivity analysis using constrained spherical deconvolution probabilistic tractography ⁵. Complete 3D histological volumes were reconstructed from a stack of cell-body (Nissl) and myelin-stained (Gallyas) 2D microscopy sections (2x2 micron in plane, 40 micron slice thickness, 400 micron interslice spacing) with optical-balancing to account for histological staining variations. All processed data were spatially aligned in a common in vivo reference space using an adapted image registration framework that was previously established for the human BigBrain project ⁶. The group level analysis was performed using matched protocols, preprocessing and analysis steps to the in vivo MicMac data.
The 15 cytoarchitectonically-defined insula subregions ² were specified on the histological images, rendered in MicMac template space, and used as seed-regions for tractography to reconstruct the connections between these subregions with other cortical regions. For the group comparison, insula subregions were transformed to native space for each subject to perform tractography. The projection endpoints of tractography results are rendered on cortical surfaces defined by CIVET-Macaque ⁷.

Results demonstrate correspondence of insula connectivity that aligns with macaque histological tract tracing studies ⁸ and previous human structural and functional connectivity studies ^9,10. The specificity of these projections, even for small subregions, was well-defined and occupied distinct patterns across the cortex. These results were repeatable for the in vivo cohort of n=16 adult macaques.

Mapping insula subregions and their connectivity throughout the brain is an important target in both humans and nonhuman primates. The MicMac workflow allows for the combination of noninvasive imaging with invasive histology markers that is impossible in humans. We demonstrated macaque insula subnetworks follow discrete organizational principles, and that the workflow shown here is translatable to a group level analysis.

Cortical Anatomy and Brain Mapping

Cortical Cyto- and Myeloarchitecture ²

White Matter Anatomy, Fiber Pathways and Connectivity ¹

Multi-Modal Imaging

Acquisition

ANIMAL STUDIES

Cellular

MRI

Multivariate

STRUCTURAL MRI

Tractography

White Matter

WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC

Workflows