Target sites for transcallosal fibers in human visual cortex – A combined diffusion and polarized light imaging study

Caspers, Svenja; Axer, Markus; Caspers, Julian; Jockwitz, Christiane; Jütten, Kerstin; Reckfort, Julia; Gräßel, David; Amunts, Katrin; Zilles, Karl

doi:10.1016/j.cortex.2015.01.009

Cited by 37 publications

(42 citation statements)

References 87 publications

(127 reference statements)

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“…A model focused on the contribution of the constituent physiological characteristics of white matter would be ideal for future applications of the watershed model, e.g. to test the complementary roles of axonal structure vs. myelin fraction (Caspers et al, 2015, Seehaus et al, 2015). Because our model does not make specific predictions for specific cellular constituents (e.g., water fraction, axonal diameter, myelin density), we favour the use of a simple tensor measure of diffusion organisation, fractional anisotropy (FA).…”

Section: Methods and Experimental Proceduresmentioning

confidence: 99%

A watershed model of individual differences in fluid intelligence

et al. 2016

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Fluid intelligence is a crucial cognitive ability that predicts key life outcomes across the lifespan. Strong empirical links exist between fluid intelligence and processing speed on the one hand, and white matter integrity and processing speed on the other. We propose a watershed model that integrates these three explanatory levels in a principled manner in a single statistical model, with processing speed and white matter figuring as intermediate endophenotypes. We fit this model in a large (N=555) adult lifespan cohort from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) using multiple measures of processing speed, white matter health and fluid intelligence. The model fit the data well, outperforming competing models and providing evidence for a many-to-one mapping between white matter integrity, processing speed and fluid intelligence. The model can be naturally extended to integrate other cognitive domains, endophenotypes and genotypes.

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Section: Methods and Experimental Proceduresmentioning

confidence: 99%

A watershed model of individual differences in fluid intelligence

et al. 2016

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“…The results greatly benefit from the application of automated high-throughput microscopy instruments, such as knife-edge scanning microscopy, 40 micro-optical sectioning tomography, 41 or light-sheet fluorescence microscopy 42 in Figure 4B,C,D, D being an enlarged view of the border region in C; the color wheel in C also applies to D). 24 while V1 and V2 can be separated in all modalities, note the particular change in fiber architecture at the border region, already visible in the myeloarchitectonic stain as the fringe area (Randsaum, Rs) and the border tuft (Grenzbüschel, Gb), but even better delineated with the transcallosal fiber bundle entering the border tuft and reaching layers I and II, as revealed by 3D-PLI combination with high-end labeling and tissue preparation techniques. 34,35,43 The combination of imaging during or before sectioning provides nearly distortion-free datasets.…”

Section: The Challenges Of Human Brain Microscopymentioning

confidence: 91%

“…23 Determining the exact target sites of fiber bundles as they leave the white matter and enter the cortex is difficult, and requires high-angular resolution diffusion imaging protocols. 24 Considering theories on cortical folding and connectivity, it is of particular interest to understand which sites of the cortex (i.e. gyri or sulci) are connected to which other sites.…”

Section: Current Frontiers In Diffusion Imagingmentioning

confidence: 99%

“…3D-PLI has successfully been applied to large-area cryostat sections of mammalian brains (rodents, non-human primates, and humans) utilizing rotating polarization microscopes of different types, all measuring in light transmittance mode. 24,[56][57][58][59][60] In a sense, the basic measurement concept can be considered a "classical approach," since the first observations on the structure of the white matter using polarization microscopy had already been reported during the 19th century. 61,62 This included descriptions of changes in the birefringence property of myelinated nerve fibers in pathological cases.…”

Section: D-polarized Light Imagingmentioning

confidence: 99%

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Decoding the microstructural correlate of diffusion MRI

Caspers

Axer

2017

NMR in Biomedicine

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Diffusion imaging has evolved considerably over the past decade. While it provides valuable information about the structural connectivity at the macro- and mesoscopic scale, bridging the gap to the microstructure at the level of single nerve fibers poses an enormous challenge. This is particularly true for the human brain with its large size, its large white-matter volume and availability of histological techniques for studying human whole-brain sections and subsequent 3D reconstruction. Classic post-mortem techniques for studying the fiber architecture of the brain, such as myeloarchitectonic staining or dye tracing, are complemented by novel histological approaches, such as 3D polarized light imaging or optical coherence tomography, enabling unique insight into the fiber architecture from large fiber bundles within deep white matter to single nerve fibers in the cortex. The present review discusses the benefits and challenges of these latest developments in comparison with the classic techniques, with particular focus on the mutual exchange between in vivo and post-mortem diffusion imaging and post-mortem microstructural approaches for understanding the wiring of the brain across different scales.

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“…3D-PLI utilizes the birefringence of myelinated and to a minor extent also unmyelinated axons in histological sections to contrast fibers with nerve cell bodies or glial cells and to determine their spatial courses in a form of 3D fiber orientation vectors. Apparently, 3D-PLI images disclose an intriguing fiber architecture, which integrates classic myeloarchitecture [6] with tissue anisotropy as revealed by diffusion magnetic resonance imaging on a microscopic level [3,5,7,8]. 3D-PLI has an obvious important bridging function between the macroscopic and the microscopic world of fiber architecture, i.e., between fiber pathways and single fibers.…”

Section: D Polarized Light Imaging In a Nutshellmentioning

confidence: 99%

3D Polarized Light Imaging Portrayed: Visualization of Fiber Architecture Derived from 3D-PLI

Schubert¹,

Axer²,

Pietrzyk³

et al. 2018

High-Resolution Neuroimaging - Basic Physical Principles and Clinical Applications

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Abstract3D polarized light imaging (3D-PLI) is a neuroimaging technique that has recently opened up new avenues to study the complex architecture of nerve fibers in postmortem brains at microscopic scales. In a specific voxel-based analysis, each voxel is assigned a single 3D fiber orientation vector. This leads to comprehensive 3D vector fields. In order to inspect and analyze such high-resolution fiber orientation vector field, also in combination with complementary microscopy measurements, appropriate visualization techniques are essential to overcome several challenges, such as the massive data sizes, the large amount of both unique and redundant information at different scales, or the occlusion issues of inner structures by outer layers. Here, we introduce a comprehensive software tool that is able to visualize all information of a typical 3D-PLI dataset in an adequate and sophisticated manner. This includes the visualization of (i) anatomic structural and fiber architectonic data in one representation, (ii) a large-scale fiber orientation vector field, and (iii) a clustered version of the field. Alignment of a 3D-PLI dataset to an appropriate brain atlas provides expert-based delineation, segmentation, and, ultimately, visualization of selected anatomical structures. By means of these techniques, a detailed analysis of the complex fiber architecture in 3D is feasible.

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Target sites for transcallosal fibers in human visual cortex – A combined diffusion and polarized light imaging study

Cited by 37 publications

References 87 publications

A watershed model of individual differences in fluid intelligence

A watershed model of individual differences in fluid intelligence

Decoding the microstructural correlate of diffusion MRI

3D Polarized Light Imaging Portrayed: Visualization of Fiber Architecture Derived from 3D-PLI

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