scholarly journals A Protocol for Cortical Type Analysis of the Human Neocortex Applied on Histological Samples, the Atlas of Von Economo and Koskinas, and Magnetic Resonance Imaging

2020 ◽  
Vol 14 ◽  
Author(s):  
Miguel Ángel García-Cabezas ◽  
Julia Liao Hacker ◽  
Basilis Zikopoulos

The human cerebral cortex is parcellated in hundreds of areas using neuroanatomy and imaging methods. Alternatively, cortical areas can be classified into few cortical types according to their degree of laminar differentiation. Cortical type analysis is based on the gradual and systematic variation of laminar features observed across the entire cerebral cortex in Nissl stained sections and has profound implications for understanding fundamental aspects of evolution, development, connections, function, and pathology of the cerebral cortex. In this protocol paper, we explain the general principles of cortical type analysis and provide tables with the fundamental features of laminar structure that are studied for this analysis. We apply cortical type analysis to the micrographs of the Atlas of the human cerebral cortex of von Economo and Koskinas and provide tables and maps with the areas of this Atlas and their corresponding cortical type. Finally, we correlate the cortical type maps with the T1w/T2w ratio from widely used reference magnetic resonance imaging scans. The analysis, tables and maps of the human cerebral cortex shown in this protocol paper can be used to predict patterns of connections between areas according to the principles of the Structural Model and determine their level in cortical hierarchies. Cortical types can also predict the spreading of abnormal proteins in neurodegenerative diseases to the level of cortical layers. In summary, cortical type analysis provides a theoretical and practical framework for directed studies of connectivity, synaptic plasticity, and selective vulnerability to neurologic and psychiatric diseases in the human neocortex.

2003 ◽  
Vol 211 (1-2) ◽  
pp. 75-80 ◽  
Author(s):  
Mariana Bendersky ◽  
Carlos Rugilo ◽  
Silvia Kochen ◽  
Gustavo Schuster ◽  
Roberto E.P. Sica

1996 ◽  
Vol 25 ◽  
pp. S267
Author(s):  
Seiki Konishi ◽  
Ryuichi Yoneyama ◽  
Hiroyuki Itagaki ◽  
Idai Uchida ◽  
Hideki Kato ◽  
...  

2017 ◽  
Vol 50 (5) ◽  
pp. 285-290 ◽  
Author(s):  
Tejeshwar Singh Jugpal ◽  
Rashmi Dixit ◽  
Anju Garg ◽  
Swati Gupta ◽  
Virendra Jain ◽  
...  

Abstract Objective: To describe the spectrum of magnetic resonance imaging (MRI) findings in patients with neurological manifestations of dengue. Materials and Methods: We included nine patients with dengue fever (three females and six males; age range, 9–30 years), all of whom presented with neurological manifestations. The MRI examinations, performed in 1.5 T or 3 T scanners, included T1-weighted, T2-weighted, and fluid-attenuated inversion recovery (FLAIR) sequences. Diffusion-weighted imaging with apparent diffusion coefficient mapping was also employed. Fast low-angle shot and susceptibility-weighted gradient-recalled echo sequences, as well as contrast-enhanced T1-weighted scans, were also obtained in order to assess parenchymal enhancement. MRI scans were analyzed for lesion distribution and imaging features. Results: All patients showed areas of altered signal intensity that appeared as hyperintensity on T2-weighted and FLAIR sequences. The most commonly affected site was the basal ganglia-thalamus complex. Other affected sites were the cerebellum, cerebral cortex, white matter, and brainstem. In all cases, we observed patchy areas of restricted diffusion and focal areas of hemorrhage. Conclusion: Dengue encephalitis commonly affects the basal ganglia, thalamus, cerebellum, cerebral cortex, and white matter. Therefore, MRI should be an indispensable part of the evaluation of patients with neurological complications of dengue fever.


2021 ◽  
Author(s):  
Yohan J. John ◽  
Basilis Zikopoulos ◽  
Miguel Ángel García-Cabezas ◽  
Helen Barbas

AbstractHigh-level characterizations of the primate cerebral cortex sit between two extremes: on one end the cortical mantle is seen as a mosaic of structurally and functionally unique areas, and on the other it is seen as a uniform six-layered structure in which functional differences are defined solely by extrinsic connections. Neither of these extremes captures the crucial neuroanatomical finding: that the cortex exhibits systematic gradations in architectonic structure. These gradations have been shown to predict cortico-cortical connectivity, which in turn suggests powerful ways to ground connectomics in anatomical structure, and by extension cortical function. A challenge to more widespread use of this concept is the labor-intensive and invasive nature of histological staining, which is the primary means of recognizing anatomical gradations. Here we show that a novel computational analysis technique can be used to derive a coarse-grained picture of cortical variation. For each of 78 cortical areas spanning the entire cortical mantle of the rhesus macaque, we created a high dimensional set of anatomical features derived from captured images of cortical tissue stained for myelin and SMI-32. The method involved semi-automated de-noising of images, and enabled comparison of brain areas without hand-labeling of features such as layer boundaries. We applied nonmetric multidimensional scaling (NMDS) to the dataset to visualize similarity among cortical areas. This analysis shows a systematic variation between weakly laminated (limbic) cortices and sharply laminated (eulaminate) cortices. We call this smooth continuum the ‘cortical spectrum’. We also show that this spectrum is visible within subsystems of the cortex: the occipital, parietal, temporal, motor, prefrontal, and insular cortices. We compared the NMDS-derived spectrum with a spectrum produced using T1- and T2-weighted magnetic resonance imaging (MRI) data derived from macaque, and found close agreement of the two coarse-graining methods. This evidence suggests that T1/T2 data, routinely obtained in human MRI studies, can be used as an effective proxy for data derived from high-resolution histological methods. More generally, this approach shows that the cortical spectrum is robust to the specific method used to compare cortical areas, and is therefore a powerful tool to understand the principles of organization of the primate cortex.


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