Abstract

For over a century, researchers have examined the functional relevancy of white matter bundles. Consequently, many large-scale bundles spanning several centimeters have been associated in their entirety with specific brain functions, such as language or attention. However, these coarse structural–functional relationships are at odds with modern understanding of the fine-grained functional organization of human cortex, such as the mosaic of category-selective regions in ventral temporal cortex. Here, we review a multimodal approach that combines fMRI to define functional regions of interest within individual’s brains with dMRI tractography to identify the white matter bundles of the same individual. Combining these data allows to determine which subsets of streamlines within a white matter bundle connect to specific functional regions in each individual. That is, this approach identifies the functionally defined white matter sub-bundles of the brain. We argue that this approach not only enhances the accuracy of interpreting the functional relevancy of white matter bundles, but also enables segmentation of these large-scale bundles into meaningful functional units, which can then be linked to behavior with enhanced precision. Importantly, this approach has the potential for making new discoveries of the fine-grained functional relevancy of white matter connections in the visual system and the brain more broadly, akin to the flurry of research that has identified functional regions in cortex.

Highlights

  • The white matter of the human brain contains a complex architecture of structural connections of different length and size that connect brain regions and enable them to communicate with each other

  • DMRI studies have examined the relationship between behavioral metrics and diffusion metrics of bundles) to link white matter fascicles to brain function

  • FSuB studies using classified tractograms (Yeatman et al 2013; Lerma-Usabiaga et al 2018; Grotheer et al 2019) revealed a consistent set of bundles that contain functionally defined white matter sub-bundles (fSuB) of the VWFA. These consistent findings across independent researchers, which used different methods to define functional regions of interest (fROI), generate tractograms, and intersect the two, provides a striking example of the reliability and robustness of the fSuB approach. These studies have generated important conceptual advances by: (1) showing that the VWFA contains two subregions that have distinct fSuB (the anterior VWFA connects predominantly to the posterior arcuate fasciculus and the posterior VWFA to the vertical occipital fasciculus (Lerma-Usabiaga et al 2018)), (2) identifying the bundles that connect the VWFA to other regions of the reading network (Grotheer et al 2019), and (3) showing that fSuB related to reading and mathematical processing are spatially and structurally segregated within the arcuate fasciculus and the superior longitudinal fasciculus (Grotheer et al 2019; Fig. 2c,d)

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Summary

Introduction

The white matter of the human brain contains a complex architecture of structural connections of different length and size that connect brain regions and enable them to communicate with each other. These examples underscore that delineations of large-scale bundles into sub-bundles defined by distinct structural properties, is a promising data-driven approach to gain a finer grained understanding of the organization and functional relevancy of white matter connections (see Schurr et al 2018, 2019, 2020).

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