The Relationship Between Axon Density, Myelination, and Fractional

The Relationship Between Axon Density, Myelination, and Fractional

Cerebral Cortex, 2020;00: 1–15 doi: 10.1093/cercor/bhz221 Original Article Downloaded from https://academic.oup.com/cercor/advance-article-abstract/doi/10.1093/cercor/bhz221/5652191 by guest on 10 February 2020 ORIGINAL ARTICLE The Relationship Between Axon Density, Myelination, and Fractional Anisotropy in the Human Corpus Callosum Patrick Friedrich 1,2,*, Christoph Fraenz 1, Caroline Schlüter 1, Sebastian Ocklenburg1, Burkhard Mädler 3, Onur Güntürkün1 and Erhan Genç1 1Department of Psychology, Institute of Cognitive Neuroscience, Biopsychology, Ruhr University Bochum, 44801 Bochum, Germany 2Brain Connectivity and Behaviour Laboratory (BCBLab), Sorbonne Universities, 75013 Paris, France 3Health Systems Department, Philips GmBH, 22335 Hamburg, Germany. Address correspondence to Patrick Friedrich, Fakultät für Psychologie, Abteilung Biopsychologie, Institut für Kognitive Neurowissenschaft, Ruhr-Universität Bochum, Universitätsstraße 150, 44780 Bochum, Germany. Email: [email protected] Abstract The corpus callosum serves the functional integration and interaction between the two hemispheres. Many studies investigate callosal microstructure via diffusion tensor imaging (DTI) fractional anisotropy (FA) in geometrically parcellated segments. However, FA is influenced by several different microstructural properties such as myelination and axon density, hindering a neurobiological interpretation. This study explores the relationship between FA and more specific measures of microstructure within the corpus callosum in a sample of 271 healthy participants. DTI tractography was used to assess 11 callosal segments and gain estimates of FA. We quantified axon density and myelination via neurite orientation dispersion and density imaging (NODDI) to assess intra-neurite volume fraction and a multiecho gradient spin-echo sequence estimating myelin water fraction. The results indicate three common factors in the distribution of FA, myelin content and axon density, indicating potentially shared rules of topographical distribution. Moreover, the relationship between measures varied across the corpus callosum, suggesting that FA should not be interpreted uniformly. More specific magnetic resonance imaging-based quantification techniques, such as NODDI and multiecho myelin water imaging, may thus play a key role in future studies of clinical trials and individual differences. Key words: corpus callosum, diffusion MRI, microstructure, myelin water imaging, neurite density Introduction 2017). Due to its topological organization, the corpus callosum With about 200 million axons, the corpus callosum is the largest serves different cognitive functions (Hofer and Frahm 2006), commissural fiber bundle in mammals (Aboitiz et al. 1992)and ranging from perceptual information transfer (Genc et al. 2011a, thus a central factor for interhemispheric transmission (van 2011b; Horowitz et al. 2015) and motor inhibition (Wahl et al. der Knaap and van der Ham 2011) and functional hemispheric 2007) to complex domains such as working memory (Siffredi asymmetries (Ocklenburg et al. 2016; Ocklenburg and Güntürkün et al. 2017) and language (Friedrich et al. 2017; Hinkley et al. 2016). © The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: [email protected]. 2 Cerebral Cortex, 2020, Vol. 00, No. 00 Patient studies underline the importance of the corpus cal- controversy about FA’s major neurobiological contributor, with losum for interhemispheric processes. For instance, studies on the two candidates being myelination and fiber geometry. acallosal patients reveal reductions in interhemispheric infor- On the one hand, some studies suggest a strong link between mation transfer (Fischer et al. 1992), motor suppression (Genc FA and myelin (Bengtsson et al. 2005; Boorman et al. 2007; et al. 2015), and reduced language asymmetries (Ocklenburg Fleming et al. 2010; Johansen-Berg et al. 2007; Kanai et al. 2010; et al. 2015) when callosal connections are absent. Given that Rudebeck et al. 2009; Scholz et al. 2009; Tomassini et al. 2011; the callosal connections show a topological organization (Hofer Wahl et al. 2007). For instance, in a study of Sampaio-Baptista and Frahm 2006), studies on patients with partial sectioning et al. (2013), rats were trained in a motoric task, which induces Downloaded from https://academic.oup.com/cercor/advance-article-abstract/doi/10.1093/cercor/bhz221/5652191 by guest on 10 February 2020 of specific callosal regions gave direct evidence for the func- plastic changes in the sensorimotor cortex contralateral to the tional heterogeneity of its constituting parts. Moreover, callosal trained limb. Comparing the training group with a control group regions do not only vary regarding their cortical termination via diffusion MRI revealed significantly higher FA values in white regions but also in their fiber architecture. In a histological matter subjacent to the sensorimotor cortex. Importantly, a postmortem study, Aboitiz et al. (1992) investigated the regional subsequent immunohistological analysis revealed an increase differentiation of the density of large and thin diameter fibers in myelin staining in the WM underneath the motor cortex. of the human corpus callosum. Fibers with a diameter below Moreover, both FA and myelin staining density were signifi- 1 μm densely populated the anterior (genu) and posterior (sple- cantly correlated with the learning rate in the motor task and nium) parts of the corpus callosum with less density in the thus suggesting an association between FA and myelin. Com- callosal midbody. Complementarily, the density of thick fibers plimentarily, a study with patients suffering from poisoning- (diameter above 3 μm) was low in the genu and splenium but induced demyelination showed a significant negative corre- showed a peak in the midbody. Microstructural factors such lation between FA values in the centrum semiovale and the as axonal diameter and myelination strongly determine the concentration of myelin basic protein in the cerebrospinal fluid speed of information transmission by influencing the conduc- (CSF) (Beppu et al. 2012). This evidence suggests that myelination tion velocity of a given axon (Caminiti et al. 2013; Knaap et al. can modulate the degree of anisotropy. However, other stud- 2005). Importantly, the topological differences in microstruc- ies indicate that myelination is not necessary for significant tural factors are functionally relevant. The shortest callosal anisotropy (Beaulieu 2002; Genc et al. 2011b; Takahashi et al. conduction delays in both human and macaque are for motor, 2002). somatosensory, and premotor areas, whereas longer conduc- On the other hand, some studies suggest other factors to be tion delays are evident in parietal, temporal, and visual areas important for FA rather than myelination (Dougherty et al. 2007; (Caminiti et al. 2013). Elmer et al. 2011; Genc et al. 2011a; Hanggi et al. 2010; Imfeld Although the architecture of axons cannot be investigated et al. 2009; Jancke et al. 2009; Tuch et al. 2005; Westerhausen in living humans directly, magnetic resonance imaging (MRI) et al. 2006). Using a choice reaction time task, Tuch et al. (2005) techniques allow the quantification of microstructural integrity showed a positive correlation between reaction time and FA based on diffusion. The most commonly used method is values. This positive correlation, however, is in conflict with diffusion tensor imaging (DTI), in which water diffusivity the myelin hypothesis: Increased myelin thickness should cause is modeled into isotropic, freely moving, and anisotropic increased FA, which in turn should result in faster conduction diffusivity (Basser et al. 1994; Le Bihan 2003; Zarei et al. 2006). The velocity and thus dictating a negative relationship between FA functionality of DTI is 2-fold. First, fiber bundles can be virtually and reaction time. Therefore, the authors suggested that prop- reconstructed based on the measurement of diffusivity along erties of fiber geometry, such as axon diameter or axon density, multiple directions. Second, diffusion properties of single voxels may be reflected by FA (Tuch et al. 2005). Concordantly, a recent can be quantified in terms of different metrics. In turn, these study that investigated white matter in schizophrenia showed metrics represent estimates of the microstructural integrity a positive association between FA and fiber density in white within a given voxel. The most widely used metric is fractional matter regions that differ between patients and healthy controls anisotropy (FA), which represents the degree of directed water (Grazioplene et al. 2018). Besides the link between FA values diffusion. and neural microstructure, FA may also vary as a function of FA is a widely used measure in cognitive and clinical neu- macrostructural fiber complexity, since FA is based on the diffu- roscience. For instance, clinical studies demonstrate decreased sion tensor’s geometry and thus decreased in areas containing FA values in patients suffering from neurological diseases, such high number of fiber crossings (Basser 1995; Behrens et al. 2007; as Alzheimer’s disease (Teipel et al. 2014), Parkinson’s disease Riffert et al. 2014). (Lee et al. 2011), and amyotrophic lateral sclerosis (Budrewicz FA is a widely used measure in neuroscience; thus, it et al. 2016), as well as in stroke patients (Puig et al. 2013; Yang is important to understand its physiological foundation. et al. 2015).

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