No abstract

The layer composition of the cerebral cortex represents a unique anatomical fingerprint of brain development, function, connectivity and pathology. Historically the cortical layers were investigated solely ex-vivo using histological means, but recent magnetic resonance imaging (MRI) studies suggest that T1 relaxation images can be utilized to separate the layers. Despite technological advancements in the field of high resolution MRI, accurate estimation of whole brain layer composition has remained limited due to partial volume effects, leaving some layers far beyond the image resolution. In this study we offer a simple and accurate method for layer composition analysis, resolving partial volume effects and cortical curvature heterogeneity. We use a low resolution echo planar imaging inversion recovery (EPI IR) MRI scan protocol that provides fast acquisition (~12 minutes) and enables extraction of multiple T1 relaxation time components per voxel, which are assigned to types of brain tissue and utilized to extract the subvoxel composition of each T1 layer. While previous investigation of the layers required the estimation of cortical normals or smoothing of layer widths (similar to VBM), here we developed a sphere-based approach to explore the inner mesoscale architecture of the cortex. Our novel algorithm conducts spatial analysis using volumetric sampling of a system of virtual spheres dispersed throughout the entire cortical space. The methodology offers a robust and powerful framework for quantification and visualization of the layers on the cortical surface, providing a basis for quantitative investigation of their role in cognition, physiology and pathology.

In 1991, Felleman and Van Essen published their seminal study regarding hierarchical processing in the primate cerebral cortex. Their work encompassed a widescale analysis of connections reported through tracing between 35 regions in the macaque visual cortex, extending from cortical regions to the laminar level. In this work, we revisit laminar-level connectivity in the macaque brain using a whole-brain MRIbased approach. We use multi-modal ex-vivo MRI imaging of the macaque brain in both white and grey matter, which are then integrated via a simple model of laminar connectivity. This model uses a granularity-based approach to define a set of rules that expands cortical connections to the laminar level. Different fiber tracking routines are then examined in order to explore the ability of our model to infer laminar connectivity. The network of macaque cortical laminar connectivity resulting from the chosen routine is then validated in the visual cortex by comparison to findings from Felleman and Van Essen with an 83% accuracy level. By using a more comprehensive definition of the cortex that addresses its heterogenous laminar composition, we can explore a new avenue of structural connectivity on the laminar level.

No abstract

Over the past two centuries, great scientific efforts have been spent on deciphering the structure and function of the cerebral cortex using a wide variety of methods. Since the advent of MRI neuroimaging, significant progress has been made in imaging of global white matter connectivity (connectomics), followed by promising new studies regarding imaging of grey matter laminar compartments. Despite progress in both fields, there still lacks mesoscale information regarding cortical laminar connectivity that could potentially bridge the gap between the current resolution of connectomics and the relatively higher resolution of cortical laminar imaging. Here, we systematically review a sample of prominent published articles regarding cortical laminar connectivity, in order to offer a simplified data-driven model that integrates white and grey matter MRI datasets into a novel way of exploring whole-brain tissue-level connectivity. Although it has been widely accepted that the cortex is exceptionally organized and interconnected, studies on the subject display a variety of approaches towards its structural building blocks. Our model addresses three principal cortical building blocks: cortical layer definitions (laminar grouping), vertical connections (intraregional, within the cortical microcircuit and subcortex) and horizontal connections (interregional, including connections within and between the hemispheres). While cortical partitioning into layers is more widely accepted as common knowledge, certain aspects of others such as cortical columns or microcircuits are still being debated. This study offers a broad and simplified view of histological and microscopical knowledge in laminar research that is applicable to the limitations of MRI methodologies, primarily regarding specificity and resolution.