Cerebral White Matter Myelination and Relations to Age, Gender, and Cognition: A Selective Review

1Humans can move, think and feel in part because their brain communicates signals through neurons. Neurons align themselves in brain layers such that gray matter consists of cell bodies and dendrites, and white matter (WM) consists of neuronal fibers with varying degree of myelination that allows transfer of signals across distributed brain areas. WM accounts for more than half of the total brain volume and is involved in cognitive, affective, sensory, and motor functions. Myelination of cerebral WM changes with individual differences such as age (i.e., maturation) and learning (i.e., experience;; ) and may be gender-specific.

2Myelination of neuronal axons in the gray matter (GM) of the brain is represented by radial and horizontal axons. Radial axonal fibers extend to the cytoarchitectonic Layer II and can pass long distances (up to 2 mm) connecting pyramidal neurons from the deeper layers with the cortical surface. Horizontal or tangential fibers are short-distance cortical axons, which originate mainly from inhibitory interneurons and lie in the two bands of in cortical layers IV and V, in Exner’s stripe within the molecular Layer I, and late-myelinated U-fibers located within the superficial WM outside the GM. Radial fibers can contain unmyelinated axons, which form temporary synaptic connections to local dendrites. Rate of myelination in short association fibers is region-specific, and is concurrent with the developmental trajectories of cognitive and motor skills.

3The speed and timing of myelination of neuronal axons within association, projection, and commissural fiber tracts that comprise cerebral WM reflect their position in the functional hierarchy. For example, myelination of the motor root fibers is faster and shorter than that of sensory roots. In an adult brain, there are three myeloarchitectonic regions, which myelinate with different cycles as distinct tectogenetic units. A median periventricular zone comprises the median thalamus and the hypothalamus, the hippocampus, and the hippocampal rudiment and septal area. A paramedian (limbic) zone includes the paramedian thalamus, subthalamic region, the internal capsule, and the pallidum and striatum with the amygdala and claustrum. A supralimbic zone, including the bulk of the WM of the frontal, parietal, and temporal lobes and respective opercula.

4Quantitative evaluation of WM volume and microstructural properties of myelinated fiber bundles is critical for understanding developmental trajectories in health and disease. Progressive myelination of WM pathways throughout infancy, childhood, and adolescence and into adulthood is concurrent with pronounced changes in cognitive abilities due to more rapid neural communication and integration of the information across functionally related brain regions.

5White matter pathways in the brain are largely represented by association, commissural and projection fibers. Association fibers connect close and distant brain areas within the same hemisphere and include the superior longitudinal fasciculus (SLF), arcuate fasciculus (AF), cingulum, inferior longitudinal fasciculus (ILF), inferior fronto-occipital fasciculus (IFOF), uncinate fasciculus (UF), middle longitudinal fasciculus (MdLF), and frontal aslant tract (FAT).

6Commissural pathways connect the two hemispheres and are represented by the corpus callosum (CC), the anterior and posterior commissures, the hippocampal commissure, the habenular commissure, and the hypothalamic and cerebellar commissures. Commissural pathways play a critical role in the integration and transfer of the information between the motor, perceptual, and cognitive modalities. Projection fibers pass through the internal capsule, corona radiata, cerebral peduncles, and brainstem to connect the cerebral cortex to other subcortical structures, such as spinal cord, deep cerebral nuclei, and brainstem nuclei, forming bidirectional (i.e., ascending and descending) connections. Output from the hippocampus to the cortex is formed by the fornix, which begins in the hippocampus and passes longitudinally toward the diencephalon and basal forebrain, arching over the thalamus. Myelination cycles of the association pathways are protracted compared to commissural and projection fibers, as they connect cortical regions, providing functional coherence between brain areas.

7Many studies focused on WM development and effects of WM lesions and cognitive impairments. Fewer studies investigate typical maturation of WM tracts in relation to cognitive functions. Literature associated with cerebral WM covers various pockets of knowledge such as methods of assessment, different conceptions of anatomical characteristics of fiber tracts, developmental effects, gender effects, and their association to mental function. Critically, a synthesis of the literature is lacking and aggregation of topics can help generate hypotheses for future research and create links between practice and research. Due to space limitations this review focuses on the most popular methods for assessing myelination, identifies anatomical considerations of nine fiber tracts, and presents current knowledge on developmental trajectories in relation to individual differences associated with age, gender, and cognition. Specifically, we cover eight major association tracts, SLF, AF, cingulum, ILF, IFOF, UF, MdLF, FAT; and one major commissural fiber system, the CC, which plays a critical role in the interhemispheric integration and transfer of the information. Although different methods exist that directly or indirectly assess microstructural properties of the WM, the most popular at this time is diffusion tensor imaging (DTI), thus, the review of individual differences related to age, gender and cognition focuses mainly on the DTI metrics, emphasizing its advantages, disadvantages, and research gaps for future studies.

8The classic methods used for myelination assessment and investigation of WM was postmortem histological staining with hematoxylin/eosin, the Luxol fast blue technique, and subsequent immunohistochemical staining for myelin basic protein and myelin-associated glycoprotein. Critically, these methods cannot be used for in vivo studies. The development of non-invasive magnetic resonance imaging (MRI) techniques made it possible to indirectly assess myelination and other microstructural indices in the living brain. These methods include DTI, Myelin Water Imaging (MWI), and Magnetization Transfer Imaging (MTI), g-ratio imaging, and myelin mapping.

9Diffusion tensor imaging is one of the most popular noninvasive indirect imaging methods used to assess microstructure and orientation of myelinated WM fibers. Diffusion MRI (dMRI) allows for investigation of the microstructure of the tissues by measuring diffusion of water molecules within the tissue considering their interaction with biological membranes and macromolecules and has been widely used to study individual differences in WM microstructure related to neurological and psychiatric conditions, as well as in healthy brains.

10Water diffusion can be characterized by the diffusion coefficient, D, (mm2/s), which links diffusive flux and concentration gradient. Diffusion of water molecules in a solution is influenced by intermolecular interactions, temperature, molecular weight, and various active processes within the tissue. Isotropic diffusion is described by a single apparent diffusion coefficient, which characterizes the interaction between the diffusing molecules and cellular structures. In the brain’s WM, especially in highly myelinated regions, water diffusion is anisotropic (i.e., it is restricted by axonal membranes; ) and can be described by a diffusion tensor, which replaces the scalar diffusion coefficient. The main direction of anisotropic diffusion within WM reflects fiber orientation, and, therefore, structural characteristics of a given brain region can be quantitatively determined by measuring water diffusion.

11The displacement of the molecules is modeled using three-dimensional Gaussian distribution. The diffusion tensor model is fitted using multi-linear regression; to estimate diffusion tensor, diffusion gradients must be applied at least along six noncollinear, noncoplanar directions. The diffusion tensor determines three orthogonal eigenvectors and associated eigenvalues (λ1, λ2, and λ3), which describe the diffusivity in the direction of each eigenvector. The direction of the main eigenvector corresponds to the direction of the fastest diffusion and determines the axis of a given fiber tract in the regions where the WM tracts do not branch and cross.

12Diffusion tensor may be geometrically represented as an ellipsoid whose axes are of the length and are aligned with the eigenvectors. The eigenvalues of the diffusion tensor can be used to estimate widely used diffusion parameters, including (1) the mean diffusivity (MD), which reflects the total diffusion in a voxel, (2) longitudinal or axial diffusivity (AD), which is equal to the eigenvalue corresponding to the longest axis (λ∥λ1, assuming λ1≥λ2≥λ3≥0), (3) transverse or radial diffusivity (RD), which reflects the diffusion in the transverse plane and may indicate changes in axonal diameter, and (4) fractional anisotropy (FA), which characterizes the eccentricity of the diffusion ellipsoid and provides quantitative measure of the shape of the diffusion ranging from 0 to 1. MD is an inverse measure of membrane density and spacing between axons, which reflects the directionally invariant overall diffusion rate. Notably, MD is similar in white and gray matter. FA reflects the difference in the shape of the tensor ellipsoid between a perfect sphere and an ellipsoid that describes anisotropic diffusion.

13The diffusion of water molecules is measured using the pulsed-gradient, spin echo pulse sequence with a single-shot echo-planar imaging. Fiber orientation may be visualized using color-coding in which blue color corresponds to superior to inferior direction, red color reflects left to right orientation, and green denotes anterior to posterior direction. FA values are usually reflected by the brightness of the color. Fiber trajectories are assessed using dMRI tractography, given that the orientation of the major eigenvector of the diffusion tensor is parallel to the fiber tracts (Figure 1). dMRI tractography starts at a “seed” point, that is a specified location at which the direction of the principal eigenvector is measured followed by moving a small fixed distance (≤1 mm) in that direction (tract integration). Evaluation of the fiber orientation is repeated and re-evaluated for successive small steps until the tract is terminated. dMRI tractography has a number of limitations, including the susceptibility of estimates of eigenvector directions to thermal noise, physiologic fluctuations, and image artifacts. In addition, this method is based on the assessment of the principal eigenvector, thus making it impossible to study the direction of the fiber tracts that branch or cross. Nonetheless, this technique has important advantages for imaging brain structures in vivo and is widely used in normative and clinical studies. Advances in scanning sequences and analysis approaches make DTI one of the most popular methods for assessing WM microstructure and myelination.

14Myelin Water Imaging is based on evaluation of myelin water fraction (MWF), which serves as a sensitive marker for myelin content. MWF corresponds to the fraction of water trapped by the myelin lipid bilayer and allows for quantitative assessment of changes in fiber myelination. MWI uses multi-exponential T2 relaxation data acquired with a multi-echo Gradient and Spin Echo sequence. The transverse relaxation time (T2, spin-spin relaxation time) determines the decay of transverse magnetization – the rate at which the spinning protons go out of phase with each other, i.e., lose phase coherence among the nuclei spinning perpendicularly to the main magnetic field B0. The transverse relaxation is related to the intrinsic field caused by the nearby protons. The individual nuclei within the tissue of interest precess in the transverse plane at slightly different rates so that their magnetic moments point to different directions and randomly interact with each other at the atomic or molecular level leading to the transverse decay of the MR signal and irreversible dephasing of the transverse magnetization. The exponential signal decay is therefore influenced by surrounding protons, and T2 for water trapped by the myelin sheath is shorter than T2 for extracellular or intracellular water, and decay amplitude is proportional to water amount in each medium.

15Myelin Water Imaging is obtained from T2 spectrum after the extraction of exponential components in a T2 decay curve and is computed in each voxel as the ratio between the T2 distribution area corresponding to myelin water (T2 < 40–50 ms) to the total T2 distribution area, and thus is independent from the magnetic field. Fitting T2 decay with other T2 components allows for the extraction of the signal derived from myelin water with short T2. At 3 Telsa, signal from myelin water has the shortest T2 component (< 40–50 ms;;; ). This algorithm can also be applied to calculate T2∗ and T1 spectra.

16The multicomponent model of relaxation signals evaluates the relative contributions of and interaction between multiple components, including intra- and extra-cellular water, cerebrospinal fluid, and myelin-related components (i.e., the water molecules within the myelin lipid bilayer;; ). However, to fit this model, a large number of measurements are needed leading to long acquisition times. Further, sophisticated preprocessing algorithms and long post-processing times impede the implementation of this method in pediatric imaging. Although new acquisition algorithms and processing strategies have been proposed, they still need to be validated before being introduced to routine clinical practice.

17In agreement with postmortem data documenting myelination progress with age, MWF increases in a caudo-rostral direction, following a parabolic trajectory with age. Changes in DTI indices usually exhibit linear association with age, and in studies which report non-linear relations peak age of myelination often depends on inclusion of young participants in selected WM regions. Indeed, peak age of myelination assessed by DTI indices is observed between 24 and 39 years, which is earlier than reported in MWI studies and MWF studies. The effect of age on DTI metrics is often different from that on MWF measures, showing weak or no correlations, as DTI may reflect other WM properties and components; therefore, some suggest that individual differences in myelination cannot be accurately described by variation in DTI-derived indices.

18As evidenced by developmental studies, changes in MWF usually show quadratic association with age, as has also been indicated in postmortem studies. Although DTI does show sensitivity to age-related changes in the cerebral WM, it may not be specific to myelin content. DTI metrics are significantly influenced by fiber density and orientation, as well as spatial organization (i.e., packing and crossing) and number of axons, whereas MWF reflects more closely myelin content, a hypothesis that has been validated histologically. However, the number of MWI studies investigating age-related changes in WM microstructure is limited, and recently developed MWI methods have not been validated with large normative samples and clinical settings. The computation of the MWF is also very sensitive to the acquisition parameters and computational settings, which makes it hard to compare results across studies.

19Magnetization transfer imaging is based on quantitative evaluation of magnetization exchange between spins via chemical exchange or cross-relaxation caused by spin diffusion. Spin diffusion is the quantum mechanical process by which spins can flip in a rigid soil medium and is associated with coupling between spin-lattice relaxations of different nuclei, such as macromolecular protons and water protons, in the presence of motion. Due to ultra-short transverse relaxation time T2 and low mobility of macromolecular protons associated with proteins and lipids, such as the galactocerebrosides within myelinated membranes, relaxation time of macromolecular spins cannot be directly visualized using MRI. Coupling between mobile water protons and protons associated with macromolecules results in exchange (i.e., magnetization transfer, MT), which allows for indirect imaging of these less mobile spins within the macromolecular proton fraction.

20The effect of cross relaxation in a heterogenous biological system is traditionally studied in the context of a two-pool model, which implies that a given biological system is comprised of two pools – the water protons (free pool), and protons associated with macromolecules (bound pool). These pools differ in their transverse relaxation times, with the transverse relaxation time of macromolecular protons and protons associated with biological membranes to be much smaller (< 1 ms) than that of water (> 10 ms). When two protons are close to each other, cross-relaxation between them may take place, resulting in simultaneous flips of spins via dipolar magnetic interaction. The spin-lattice relaxation in each pool is determined by a sum of two exponential decays characterized by two apparent relaxation rates.

21The excitation of the proton spins bound to macromolecules by a radiofrequency pulse results in the transfer the energy to the nearby proton spins, which is referred to as the magnetization transfer effect. Traditionally, the MT effect has been assessed using an MT ratio (MTR), which measures a relative decrease in observed signal in the saturation experiment with an off-resonance radiofrequency pulse and allows for the evaluation of myelin content in the WM. Based on MT-weighted, T1-weighted, and proton-density weighted images, it is possible to build macromolecular proton fraction (MPF) maps, which describe the proportion of macromolecular protons contributing to MT effect as a result of cross relaxation with water protons. MPF mapping is a new technique, which has been histologically validated and shows promise as a tool for accurate evaluation of fine changes in myelin content in fetal brain.

22Magnetization transfer imaging is heavily dependent on experimental conditions, including scanner type and sequence characteristics. In addition, due to the interaction with other physical parameters of a two-pool model, such as the longitudinal relaxation rate (R1 = 1/T1), which also correlates with myelin content and is sensitive to various physiological parameters, including iron and calcium levels, axon count and size, the association between MTR and myelin content in tissue is nonlinear. Further, it is argued that MTR is sensitive to macromolecules associated with other cellular components, such as cytoskeleton, and, therefore, a solution given by a two-pool seems to be insufficient to accurately access complex interactions between molecular pools in living tissue.

23Throughout development, MTR gradually increases in the posterior-to-anterior direction. Myelination rate is faster in the projection and commissural than in the association fibers, as indicated by lower MTR values in the association areas at first month of age. In the occipital and frontal regions, MTR reaches peak by 13 and 16 months, respectively. MTR in the thalamus, splenium and genu of the CC reaches 95% of the adult value by 10, 18, and 19 months, respectively. Throughout adulthood, MTR in the occipital and temporal regions slightly increases, remaining relatively stable in other areas.

24Macromolecular proton fraction in the fetal brain (18–38 weeks) is fivefold lower than in adult brain. In the brainstem, cerebellum, and thalamus it shows positive association with gestational age.

25The values of R1, which is principally sensitive to macromolecular fraction and tissue volume, reach peak between ages 30 and 50 years, and between 70 and 80 values drop substantially to values comparable to 8-year-old values. Over an 80-year period, changes in R1 follow parabolic curve, indicating a symmetric pattern of age-related changes.

26In an adult brain, R1 values vary considerably among tracts, and their mature R1 and the rate of R1 changes are different. For example, the age-related R1 growth and decline in in the cingulum and ILF are twice as higher than those of the corticospinal tract and anterior thalamic radiation. Unlike R1, the rate of change in diffusivity during development exceeds that of aging, and therefore diffusivity data, particularly MD, do not follow a symmetric parabolic pattern, but instead can be described by a Poisson curve, sharply decreasing throughout childhood and adulthood, and then slowly increasing in the third decade of life.

27Although indices associated with macromolecular content in tissues seem to provide a more accurate estimate of developmental gain and age-related decline in WM than diffusion metrics, MTI is now mostly used in clinical research, and, to date, there is not enough normative pediatric data to comprehensively describe WM changes throughout development.

28A new method which allows for the assessment of relative myelination and conduction velocity of an axon is based on the evaluation of the g-ratio (i.e., the ratio of the inner to the outer diameter of the myelin sheath; ). This method has been introduced in 2011 and was applied in full brain WM imaging in 2013. The g-ratio is quantitatively expressed as a function of the myelin volume fraction (MVF) and the axon volume fraction (AVF):

29Diffusion MRI methods are used to assess the relative AVF by measuring the shape of the displacement distribution of water molecules and evaluation of the intra-axonal volume fraction within the diffusion visible volume. The most popular diffusion models, which can be used to estimate the relative size of cellular compartments include neurite orientation density and dispersion imaging, composite hindered and restricted model of diffusion, diffusion basis, restriction spectrum imaging, and other methods described in detail in.

30Myelin volume fraction can be obtained from MT saturation index, quantitative MT imaging parameters, MTR, proton density imaging, single-point two-pool modeling, quantitative multicomponent T2 or T2∗ relaxation techniques quantifying the myelin water fraction, macromolecular pool size from quantitative MT, and single-point two-pool and inhomogeneous MT. g-ratio shows considerable variation among different fiber pathways and its values are shown to be in agreement with ex vivo histological measures. However, the accuracy of the g-ratio largely relies on the calibration procedure, since the models used to assess MVF do not consider a tissue model, as diffusion models do. Selection of an appropriate calibration approach significantly influences the obtained g-ratio, and, therefore, affects repeatability and comparability of the data.

31Despite the high potential of the g-ratio for in vivo estimation of relative myelination and the application of this method in normative and clinical studies of white matter evaluation, it has not been yet introduced into routine research practice, and the data on g-ratio changes across development are still limited.

32The developmental trajectory of the myelin g-ratio is still unknown. It is expected that g-ratio decreases over time, as axon growth rate exceeds speed of myelination. Only a few studies have examined age-related changes in g-ratio. Throughout infancy and early childhood, g-ratio logarithmically decreases, reaching theoretically predicted values. Age-related nearly-linear increase in g-ratio from 20 to 76 years of age has been demonstrated with no gender effect identified.

33An alternative method for assessing cortical myelin content, which is highly generalizable across different scanners and pulse sequences, and, thus, allows for the comparison of the data across studies, is based on combining T1-weighted (T1w) and T2-weighted (T2w) MRI to map myelin content. T1 and T2 relaxation times reflect the interaction between water and macromolecules in tissue. T1 strongly depends on membrane composition, particularly on lipid content (i.e., cholesterol and cerebroside levels; ). Image intensity (e.g., brightness of the T1w image) reflects the distribution of myelin-associated macromolecules, whereas T2 relaxation time is associated with the molecular exchange and water diffusion, such that the lower intensity of a T2w image corresponds to higher myelin content.

34The T1w/T2w index makes it possible to quantitatively assess spatial distribution of myelin, to eliminate MR-related image intensity bias, and to increase the contrast to noise ratio. Fast scanning time makes this method valuable for pediatric imaging. However, due to high sensitivity to intensity scale inconsistencies across different datasets, this method requires strict calibration, which is currently a matter of research.

35In summary, various techniques have been used to assess maturation of WM tracts in the human brain. Considerably more research is needed to replicate and validate findings across methodologies, which will lead to optimized scanning protocols for healthy and clinical signatures of WM changes. As the majority of the literature evaluates maturation of WM tracts using DTI, in what follows we focus on this literature to review considerations related with anatomical characteristics of common fiber tracts and results associated to age, gender and cognition.

36A major association WM tract that links the temporoparietal junction and parietal areas with the frontal lobe is the SLF. Three SLF branches connect the ipsilateral frontal and opercular areas to the superior parietal lobe (dorsal subdivision, SLF I), to the angular gyrus (middle branch, SLF II), and to the supramarginal gyrus (ventral subdivision, SLF III). They are comprised of the frontoparietal network of the human brain with the SLF I being symmetric between the two hemispheres, and the SLF II and SLF III demonstrating rightward lateralization. The AF is the fourth subdivision of the SLF, which links the posterior and middle superior temporal gyrus with the ventrolateral prefrontal cortex and the posterior region of Broca’s area (pars opercularis, Brodmann’s area 44;; ). However, some authors suggest that the AF is distinct from the SLF, with the AF connecting the caudal part of the superior temporal area with the dorsal prefrontal region of the cerebral cortex and comprising of the long, anterior, and posterior segments, and the SLF linking frontal and parietal cortical areas, although the anterior segment of the AF and the SLF III overlap. The branch of the SLF, which connects the temporal cortex to the inferior parietal cortex (temporoparietal subdivision, SLF TP) is considered as the fifth subcomponent, although it rarely appears in dMRI tractography studies.

37The cingulum is an association WM tract which extends sagittally and connects the orbital frontal regions with the pole, passing along the dorsal surface of the CC down the temporal lobe. This bundle is viewed as a part of the limbic system and considered one of the central components of Papez circuit, which constitutes bilateral WM pathways between the anterior thalamic nuclei and cingulate cortex, as well as the parahippocampal region and the cingulate cortex. A substantial portion of cingular association fibers that run across the sagittal plane form intracortical connections, linking the medial parts of the frontal, temporal, and parietal lobes. dMRI tractography reveals three components of the cingulum: subgenual, retrosplenial or supracallosal, and ventral parahippocampal subdivisions, which are characterized by different FA values. Based on current anatomical evidence, the cingulum can be divided into five subdivisions, including the subgenual, rostral dorsal (anterior cingulate), caudal dorsal (retrosplenial), and temporal (parahippocampal) subcomponents and midcingulate cortical area.

38The ILF is a ventral association WM tract, which connects the anterior temporal lobe, including the superior, middle, inferior temporal, and fusiform gyri, to the lingual, cuneate, lateral-occipital and occipito-polar regions of the occipital cortex. Connectivity pattern of the ILF is characterized by a significant leftward-dominance and ventral position.

39The IFOF is one of the major association fiber systems, which is recognized as a part of the dorsal visual stream. It links the occipital cortex, temporo-basal areas, and superior parietal lobe with the frontal regions, passing through the temporal lobe and insula and crossing the SLF, AF, ILF, and MdLF. High-angular-resolution diffusion imaging shows that the IFOF fibers vary in the sites of origin. Most of the fibers originate from the lateral and medial orbital frontal cortices, frontal polar cortex, including the fronto-marginal gyrus and transverse frontopolar gyrus, superior frontal gyrus and inferior frontal gyri, including the pars opercularis, pars triangularis, and pars orbitalis, and from the middle frontal gyrus. Fibers of the posterior portion of the IFOF terminate in the pericalcarine (cuneus and lingual gyrus) and fusiform gyri and occipital region, including the inferior, middle, and superior occipital lobes, with some fibers terminating in the superior parietal lobe, angular and postcentral gyri. A comprehensive study by suggests that the IFOF has at least five subcomponents characterized by different connectivity patterns, albeit other researchers divide this fasciculus into three or two subdivisions, or consider it as a whole tract.

40One of the long-range association bidirectional monosynaptic WM pathways is the UF, which connects the anterior temporal lobes and amygdala to the lateral orbitofrontal cortex and the anterior portion of the prefrontal cortex.

41Commissural pathways connect two hemispheres and are composed of the CC, the anterior and posterior commissures, the hippocampal commissure, the habenular commissure, and the hypothalamic and cerebellar commissures. As it follows from fiber location, commissural pathways play a critical role in the integration and transfer of the information between the motor, perceptual, and cognitive modalities.

42Projection fibers pass through the internal capsule, corona radiata, cerebral peduncles, and brainstem connect the cerebral cortex to other subcortical structures, such as spinal cord (SC), deep cerebral nuclei, and brainstem nuclei, forming bidirectional (ascending and descending) connections. Output from the hippocampus to the cortex is formed by the fornix which begins in the hippocampus and passes longitudinally toward the diencephalon and basal forebrain, arching over the thalamus.

43Middle longitudinal fasciculus is an association fiber tract, which was originally identified in the rhesus monkey brain, where it links the caudal and rostral portions of the STG, the caudal cingulated gyrus and the middle portion of the parahippocampal gyrus with the upper sector of the STG.

44Neither the classical, nor the contemporary fiber microdissection studies have described the anatomical structure of MdLF. The existence of the MdLF has been first documented in a DTI study by. Although DTI does not allow for an accurate tracking of the MdLF origin and destination, especially in voxels containing crossing fibers, more studies demonstrate successful delineation and differentiation of the MdLF from other ventral and dorsal association fiber pathways. Notably, human dMRI tractography and microdissection studies show prominent differences in MdLF anatomy between humans and monkeys. As such, the human MdLF was shown to link the STG with the superior parietal lobule and parietooccipital region, with only minor connections with the angular gyrus, unlike monkey brain.

45The FAT interconnects the pars opercularis and pars triangularis of the inferior frontal gyrus and the anterior insula with the supplementary motor area (SMA) and pre-SMA, and it was first identified in 2007 by and then described and named in the studies of and. In addition, it was also identified in monkey and human postmortem dissection studies.

46Maturation of fiber tracts has been documented in vitro (e.g., ). In what follows we focus on in vivo studies that use DTI to evaluate typical development identifying consistencies and inconsistencies in reports related to age, gender and cognitive abilities.

47The process of myelination follows a complex topographical and temporal pattern across development as demonstrated by histological studies. Changes in myelination are proposed to be synchronized among functionally related fiber networks. In DTI studies, WM maturation is traditionally examined by assessing the changes in several metrics, including AD and FA, which increase with age as myelin thickness and axonal diameter and density increase, and RD and MD, which are known to decrease with age.

48Critically, there is no period in development when WM microstructure in the brain is static. During childhood, adolescence, and early adulthood, WM maturation is fast and dynamic and shows pronounced increase in fiber density and myelination as indicated by an increase in FA and decrease in MD and RD. During mid-adulthood, WM structure is relatively stable, and in late adulthood, changes in WM accelerate again, reflecting degenerative processes, as indicated by a sharp reduction of FA and an increase in MD and RD.

49The speed of myelination in a given region during ontogenesis corresponds to the position of the system in the functional hierarchy. The first site of myelination is the SC. Here, myelination begins at 12–14 weeks of pregnancy. Myelination cycle of the motor root fibers is faster and shorter than that of sensory roots. The last site of myelination in adults is intracortical fibers of the cerebral cortex. Within the period between midgestation and the end of the second postnatal year, this process is characterized by the greatest rate and undergoes the most dramatic changes.

50Myelination of the cranial nerve roots terminates early in the first postnatal year. The genu of the CC is myelinated by the 6th postnatal month. In the frontal, parietal and occipital lobes, the fibers are myelinated by 8–12 months of postnatal life. In the central nervous system, sensory fibers which form the inputs to the thalamus and cerebral cortex myelinate earlier than fibers which participate in the integration of sensory information into movements. The longest myelination cycle is characteristic for the commissural and association fibers of the supralimbic zones. It exponentially continues to the years of maturity to senium. The development of the major fiber pathways from preterm age to the first postnatal age are summarized in Figure 2.

51Myelination of the cerebral WM begins in the tenth fetal month. The most rapid growth of the brain occurs during the first 3 years of life. During childhood, an increase in WM volume exceeds that of the GM. A key common trend in WM development found across the majority of studies is its non-linear pattern across childhood and adolescence, accompanied by an overall increase in FA and a decrease in MD during the first years of life, which is more pronounced during early childhood. Fibers in the left hemisphere show greater maturation rate, and changes in myelination indices demonstrate an overall posterior-to-anterior gradient. Interestingly, FA in the association tracts reaches its maximum 3–7 years before MD reaches minimum. The transition from childhood to adolescence is accompanied by a pronounced increase in FA in the major fiber tracts, including the ILF, SLF, IFOF, fornix, cingulum, UF, and all subdivisions of the CC, indicating an increase in fiber density and myelination. Changes in MD show nonlinear pattern, reaching minimum between the age of 18–41 years and then gradually increasing. Early development is characteristic for the CC and fornix, whose myelination is complete by the age of 20, whereas pathways which form frontal–temporal connections, including cingulum, UF, and SLF, demonstrate a more protracted maturation cycle, with the cingulum reaching peak FA values after 40 years.

52Myelination of the CC in children is incomplete, and with age it continues to mature, as it is one of the critical structures that sustains interhemispheric interaction. Importantly, different subdivisions of the CC demonstrate high degree of variability in size and maturation rates. Posterior and mid regions of the CC show greater dependence on age compared to anterior portion of the tract, including the rostrum and genu of the CC that reach adult size in young children, thus exhibiting anterior to posterior gradient of myelination. FA in the genu and splenium of the CC reaches peak values at 21 and 25 years, respectively, and in the body of the CC FA reaches maxima at the age of 35 years. Critically, the assessed rate and temporal pattern of development of the splenium often vary by the age range of study participants and the fitting method used to model callosal maturation.

53Findings on age-related changes in other DTI metrics, such as RD, which reflects the rate of water diffusion in the direction perpendicular to the main axis of the axon, show that the most active maturation of association and projection pathways, which maintain cortical and brainstem integration, occurs during adolescence. This is concurrent with the behavioral observations of pronounced improvements in reaction time that continue into late adolescence and adulthood. Between 10 and 12 years of age, it is estimated that brain weight reaches adult values. This period of WM maturation is accompanied by the maturation of critical cognitive functions, such as executive control and interhemispheric communication. The majority of fiber tracts, including the CC, SLF, ILF, IFOF, UF, and cingulum exhibit nonlinear developmental trajectory, as indicated by quadratic increases in FA and MD.

54In the adult brain, the three myeloarchitectonic regions myelinate at different rates. Consistent with in vitro studies, DTI studies demonstrate that myelination of most association tracts continues into the third decade of life in a well-defined order. Also, age-related decrease in myelination in these fibers is delayed. Myelination of the SC is mainly studied in animal and clinical studies. Cervical SC microstructural properties are vulnerable to aging, as FA in this subdivision shows strong negative correlation with age and it dramatically decreases after the age of 55 years. Across the SC subdivisions, FA decreases in rostral-caudal direction, whereas MD remains relatively constant. The AD in the cervical subdivision is larger in thoracis and lumbar segments, indicating the presence of large-diameter myelinated axons. Notably, higher FA in the C2–C7 of the cervical SC predicts better performance in visuomotor tracking of precision grip force. The study of demonstrated asymmetry in WM density in the cervical SC: FA was higher in the lateral portion of the SC and on the right side, compared to the medial SC and the left side, respectively. Notably, across all cervical segments, only FA in the medial SC correlated with age, indicating higher sensitivity of this subdivision to aging.

55During the transition from childhood (6–11 years) to adolescence (12–16 years), FA, fiber density and length in the SC increase, whereas MD decreases. Findings on the association between other DTI metrics and age are controversial. Some studies demonstrate an increase in AD and MD with age, whereas others find an age-related decline in diffusivity measures.

56Overall, finding on age-related changes in DTI indices in the SC are limited, and the association between SC myelination and cognitive and motor skill development is yet to be explored.

57Critically, review studies that examine normative values across development, recognize that different methodological approaches such as preprocessing, statistical analyses and age group limits contribute to result differences among studies. Specifically, they emphasize that linear models may not characterize the dynamic non-linear maturation patterns in myelination that occur across development and identify the need for improved methods. Notably, dMRI tractography results are highly dependent on optimization algorithms. One of the most advanced algorithms is the gradient-free Powell conjugate-direction algorithm, which allows for considerable improvement of run time, parameter fit, and accuracy, whereas the parameter initialization approaches provide better fit for complex models.

58Histological methods greatly contributed to the understanding of temporal pattern and regional specificity of the WM, however, data on gender differences in myelination pattern have been mostly obtained using MR-based techniques. Although male and female brains show many similarities, some studies highlight differences between the genders (e.g.,; ), yet others suggest that these differences are driven by environmental and cultural factors.

59The proton density and T2-weighted MRI data corrected for total intracranial volume demonstrate that females exhibit a higher proportion of GM, while males are characterized by a greater percentage of total WM and cerebrospinal fluid, albeit some studies indicate that these differences are insignificant. Critically, the absolute differences in brain size and regional differences in the proportions of GM and WM between males and females mostly correspond to differences in WM volume. In addition, after correcting for total cranial volume, no significant differences in the volumes of amygdala, hippocampus, and the dorsal prefrontal cortex between men and women are reported, although adult females are found to have significantly greater volume of orbitofrontal cortical region.

60Several MRI studies demonstrate that the pattern of white and gray matter maturation in certain brain regions differs in males and females. The total volumes of the cerebral gray and WM and CC show a pronounced sex-age interaction with males exhibiting a more significant age-related reduction of the gray matter and an increase in the WM volume and callosal region. According to the results of voxel-based morphometry analysis carried out by, WM volume in the frontal, temporal, parietal, occipital, and insular regions of the brain is larger in men compared to women, and only WM of the postcentral gyrus in the right parietal lobe is greater in women compared to men. However, the authors of the study did not control for the total brain volume, although they claim that these differences cannot be explained by an assumption that the brain volume of men is, in general, bigger than that of women.

61Data on gender differences in WM in frontal regions are contradictory. A study by reports that adult women have higher FA in the left frontal lobe compared to men. In addition, females exhibit a leftward frontal asymmetry in FA (i.e., higher FA values in the left hemisphere), which correlates with a better comprehension of verbal constructions and memory functioning in women, whereas males show no such asymmetry. These differences may be explained by the fact that maturation of the WM in the frontal lobes continues into late adulthood with a peak at about 45–50 years of age. A DTI study by found that adult males have higher FA values in the cerebellum and at the anterior portion of the left SLF, whereas females show greater FA values in the CC, interpreted to contribute to better interhemispheric communication and intellectual performance. Boys are also characterized by greater FA values in bilateral frontal WM, in the right AF, and in the left parietal and occipito-parietal WM. Interestingly, in the left frontal lobe, boys exhibit a positive and girls show a negative correlation between age and FA. In contrast, FA in the right AF positively correlates with age in girls and negatively in boys. In the right frontal lobe and right occipito-temporo-parietal WM girls exhibit a positive association between FA and age, whereas no significant correlation is found in boys. An MRI study of healthy children and adolescents (6–17 years; ) shows significant right > left asymmetry in the total cerebral volume, total cerebral WM, and WM of the middle and superior frontal gyri of boys, whereas girls are characterized by the same asymmetry pattern in the total cerebral WM and WM of the superior frontal gyrus. In addition, WM in the left inferior frontal gyrus shows age-dependent increase in boys, but not in girls. The authors speculate that these differences may be associated with gender effects in the development of speech and language lateralization.

62The most rapid changes in the developmental pattern of the CC occur during infancy and findings on gender influence on the structure and development of the CC are inconsistent and largely depend on method and age when the microstructure was examined. One of the factors that may cause the discrepancies in findings on gender differences in the CC microstructure and development is the size of the brain: males, on average, are characterized by larger brain size than females, and therefore the size of the CC, if not adjusted for brain size, is also larger in males. Early data show no differences in the size and shape of the splenium of the CC between males and females, irrespective of the adjustment for brain size. However, recent DTI data on callosal area and thickness from infants (6–24 months) adjusted for brain size demonstrate a higher growth rate and size in boys than in girls, although the association between the microstructural characteristics and callosal size exhibits no significant gender differences. show a significant gender-related difference in the development of the CC with age and their association with lower performance on cognitive and motor tasks observed in older adults. A DTI study by shows that girls (mean age ∼12 years) have higher FA in the splenium of the CC than boys. Interestingly, the greater size of the splenium of the CC observed at autopsy was not confirmed by an early MRI study, which, reported a gender-related difference in minimum width of the callosal body and an age-related decline in anteroposterior distance and significant intraindividual variations in callosal size and shape regardless of age or gender.

63Mechanisms that drive gender effects may rely on biological and experiential factors. Early studies suggest that differences in spatial and temporal pattern of myelination in boys and girls may be due to changes in sex steroid hormone levels during critical periods of development, accompanied by a 26-fold increase in testosterone and a 10-fold increase in estradiol level in males and females, respectively. Although steroid hormones are essential for myelination in both sexes, current research show that age-related changes and gender differences in sensitivity and responsiveness of brain structures to hormonal influences may explain different effect exerted by testosterone and estradiol on male and female brain at different stages of development.

64Estradiol is known to affect hippocampal and Schwann cell proliferation and differentiation, regulation of synaptic function, morphology, and plasticity, modulation of synaptogenesis and remodeling of neuronal circuits. Testosterone, in turn, stimulates neuronal growth at early stages of development, and both neuronal growth and myelogenesis at later stages.

65Normative values for DTI indices may differ across studies. Moreover, different imaging methods may provide different estimates of WM microstructure. For example, some DTI studies show that the CC is more myelinated in males than in females, whereas T1-weighted imaging demonstrates and opposite pattern. Maturation pattern in some fiber tracts is still poorly understood due to extant disagreements on the structure of the tracts. Further, a thorough review and meta-analyses of human MRI and postmortem data cautions that gender effects in human brains are largely based on overall brain size and in the few instances that they appear they contribute only to 1% of variance in structure. Therefore, when investigating gender-related differences in WM development and microstructure, it is important to consider differences in total brain size, and to take into account specificity of the method applied and age of the participants, since myelination rate at different developmental stages is different. Moreover, the comparison of the neuroimaging results with the post mortem findings may help to clarify the discrepancies across methods. Further research, especially longitudinal studies and meta-analyses that identify overarching patterns in the data, are needed to evaluate effects in WM between the two genders.

66White matter pathways, which connect distributed brain areas, play a fundamental role in the maintenance of higher-level cognitive functions and are pivotal for cognitive, motor, and behavioral performance. A DTI study by found an association between bimanual coordination and characteristics of WM microstructure in the CC which connects the supplementary motor area and caudal cingulate motor area. Compared to an object recognition task, high FA in the splenium and genu of the CC were associated with shorter and longer reaction times, respectively. The task on object recognition was presented from unusual viewpoints, which required transduction of the information from the right parietal cortex to the left inferior parietal cortex. Since myelin sheath increases signal transduction and its formation continues during adulthood, brain myelination plays an important role in inhibitory control and executive functions in children and adolescents, thus underlying healthy maturation.

67Research suggests that greater axonal volume and myelination in particular brain regions, including the parietal cortical areas, left superior and posterior corona radiata, and body of the CC contribute to better performance on auditory working memory tasks, such as letter-number sequencing, by sustaining higher speed of information processing. suggest that myelination and maturation of synaptic connections in fronto-parietal brain networks during adolescence is implicated in greater specialization and processing efficiency, which, in turn, mediates the development of executive functions in children and adolescents. As shown in a DTI study by, the correlation between microstructural measurements of WM in the right projection and association pathways, such as the right optic radiation, right posterior thalamus, and right medial precuneus, with visual self-paced choice task performance, reflects the fundamental role of myelination in these regions for maintenance of visuospatial attention. Notably, microstructural characteristics of WM pathways, including FA and neurite density, show a positive correlation with mathematical performance in 13-year-olds. Myelination indices in the left superior corona radiata correlate with numerical operations and mathematical reasoning, whereas WM microstructure characteristics in the left ILF show associations with numerical operations specifically.

68Myelin is a principal component of WM and it accounts for approximately 50-60% of the WM dry weight. Stimulation of oligodendrocyte precursor cells results in their transformation to mature oligodendrocytes. Although the majority of tracts are myelinated by adulthood, several WM areas, such as those in prefrontal regions and optic radiation, reach peak of myelination between the third and fourth decades of life. Some suggest that myelination is mainly driven by neuronal activity (i.e., generation and passage of action potentials along the axonal membrane), which can trigger an increase in axonal diameter. Once the axonal diameter exceeds 0.5 mcm and the number of action potentials generated along the unmyelinated axonal membrane is sufficient to stimulate conversion of oligodendrocyte precursor cells to mature cells, oligodendrocytes wrap nearby axons by myelin layers.

69In mature axons, fine tuning of myelination speed and modulation of signal transmission are controlled by changes in myelin thickness and the length of myelinated axonal regions, axonal diameter, and topographical organization of the nodes of Ranvier within the axons. Particularly, along with the number of myelin layers and internode length, node organization to a large extent determines conduction speed along myelinated axons, and modulation of the lengths of the nodes of Ranvier serves an efficient mechanism to control signal conduction.

70It is proposed that myelination can be activity-dependent (i.e., depend on electrical activity of the axon and various molecular mediators synthesized and released in response to electrical events), and activity-independent (i.e., regulated by oligodendrocytes and independent from on the axonal electrical activity; for review). An intriguing work by discusses a “smart wiring” model of myelination, which includes two phases – intrinsic and adaptive, and suggests possible mechanisms by which active axons may become more myelinated and how brain circuits may be modified in response to learning and new experience. Bechler also discusses adaptive myelination, which is provided by several properties of oligodendrocytes. Oligodendrocytes in the central nervous system are generated from special progenitor cells, which actively divide throughout the whole life. Moreover, proliferation and differentiation of oligodendrocyte precursor cells was demonstrated to improve motor learning and learning new motor skills, which in turn, changes the structure of the WM containing many late-born oligodendrocytes. Overall, brain myelination appears to be adaptive, and it may change in response to learning and new experience that relates to fiber tracts that connect brain areas associated with various cognitive, affective and motor functions.

71Therefore, research supports that increasing neuronal activity, which accompanies brain maturation and learning is the main driving force for dynamic myelination and regulation of network organization throughout lifespan. By modulating oligodendrocyte precursor cell proliferation and oligodendrocyte differentiation, increased neuronal activity ensures efficient signal transmission, fine-tuning of conduction speed, and the maintenance of circuit function. Myelin growth, in turn, promotes an additional increase in conduction velocity, thus strengthening the existing connections. This is consistent with developmental cognitive theory that proposes neuropsychological mechanisms that underlie these changes. Specifically, the Theory of Constructive Operators proposes that operators (i.e., content-free general resources represented by functional-structural constrains) regulate schemes (i.e., information bearers represented by cell assemblies and networks) that produce a mental or action output when following the principle of schematic overdetermination of performance (i.e., following a winner-takes-all approach). This framework allows for ontogenetic, biological influences to drive maturation (i.e., relate more to operators) as well as experiential opportunity to drive learning (i.e., relate more to schemes). As we overview below, structure-function relations may be supported by mechanisms associated with biological maturation and experiential learning.

72The largest fiber tract in the brain is the CC. It consists of more than 200 million axons and plays a key role in integration and interhemispheric transfer of information. Malformation of the CC results in deficits in higher-level cognitive functions and social communication, as well as in a slower rate of cognitive processing, impaired language function, abstract reasoning, and concept formation. Incomplete myelination of the CC in 6–7-year-old children is associated with behavioral abnormalities and results in impaired transfer of complex visuomotor skills learned by the dominant hand from one hemisphere to another. The observation that myelination of the anterior portion of the CC may be induced by working memory training suggests plasticity of WM microstructure in this region. Reduced integrity of the CC, in turn, may lead to working memory deficits. In particular, reduced integrity in the callosal subregions, which connect anterior and posterior parietal cortical areas, is associated with lower performance in verbal working memory tasks, and higher RD in the portion of the CC, which links anterior regions with posterior and temporal cortical areas, predicts lower performance in visuospatial working memory task. Interestingly, the length of the CC shows negative correlation with nonverbal abilities. Together with the cingulum, the CC often shows correlations with functional measures in neurological groups.

73A number of DTI studies show that the cingulum, especially its dorsal portion, is implicated in cognitive control and various executive functions, including shifting and inhibition, updating and working memory, processing speed, and sustained attention. In particular, FA in the right cingulum correlates with task performance on the Continuous Performance Test, which measures sustained attention. MD in the bilateral cingulum shows gender integrations and is associated with internalizing behavior in children and adolescents, which is more pronounced in females. Interestingly, FA in the left cingulum, as well as in the left UF, shows strong age-behavior interaction. Microstructural characteristics in the posterior cingulum also demonstrate a strong association with language (category fluency and naming to confrontation) and visual-spatial functions, whereas FA in both posterior and anterior portions of the tract are implicated in attention, executive functions, and memory assessed by free recall retention task performance and auditory verbal learning test. The strongest evidence about the contribution of the cingulum to episodic and verbal memory functions are demonstrated in clinical samples, including Alzheimer’s disease, amnestic mild cognitive impairment, cerebral small vessel disease, and acute mild traumatic brain injury. Together with the AF and UF, the microstructural properties of the cingulum are often reported to be strongly associated with psychiatric symptoms.

74An intriguing article by describes the use of a data-driven community-clustering algorithm to analyze differences in WM microstructure in children and adolescents (mean age ∼11), which identified two subgroups characterized by a prominent difference in FA in bilateral cingulum. Critically, these two brain types differed in cognitive abilities with the higher FA group exhibiting better performance in working memory and long-term memory tasks, fluid intelligence, and vocabulary. Long fibers in the dorsal cingulum run in parallel with the long-range fibers in the SLF, which, in turn, extent more laterality to the AF in each hemisphere.

75Diffusion tensor imaging studies show that the right SLF is associated with various complex cognitive functions, including attention and visuospatial abilities, whereas left SLF plays a fundamental role in language and reading skills. In adolescents, bilateral SLF is involved in verbal working memory and verbal fluency. It is proposed that the SLF consists of five branches. The SLF I is involved in the regulation of motor behavior and the initiation of motor activity. In addition, it was suggested to transfer somatosensory and kinesthetic information about location of body parts, including trunk and limbs, to the frontal regions of the brain. The SLF II sustains visual perception and it is a part of the circuit involved in visual awareness and the maintenance of attention. The SLF II fibers connecting the prefrontal cortex with the posterior parietal regions are implicated in regulation of the focusing of attention. The SLF III was found to convey higher-level somatosensory information and to be involved in gestural communication. The dorsal pathway through the lateral SLF supports articulatory function, phonological working memory, perception and production of speech. The AF is implicated in intelligence, reasoning abilities, and language processing, playing a critical role in auditory to motor connection and semantic and phonological processes associated with visual information. The indicators of WM microstructure in the left SLF demonstrate a negative association with inhibitory control, whereas in the left AF they correlate with intelligence tests and attention. Therefore, findings from the neuroimaging studies demonstrate a critical role of the SLF and AF in neurophysiological abilities and cognitive function.

76The ILF, together with the MdLF and UF, comprises the ventral stream of language processing and was found to sustain speech comprehension and general semantic processes. A proposed role of the ILF in semantic functionality is supported by neuroimaging data obtained in the study by, which demonstrates the role of the ILF in language comprehension. The ILF connectivity pattern was also shown to be leftward-lateralized and greater fiber density and myelination in this region were found to be associated with better semantic processing. Moreover, the ILF is known to be implicated in object and face recognition. Some earlier studies show that the peak of myelination in the ILF occurs at 11 years of age, whereas recent findings demonstrate that the maturation of this fiber tract continues until age of 24 years. Notably, age has a great impact on lateral tracts in dorsal areas of the brain, including the SLF, whereas the inferior regions are less affected by aging. The ILF, together with the AF, demonstrates strong functional correlations with cognitive measure in healthy individuals.

77Diffusion MRI tractography studies suggest the role of the IFOF in semantic and visual processing and attention. In particular, bilateral IFOF (especially in the left frontal and right occipital parts) is implicated in the maintenance of executive functions, whereas the parietal and insular parts of the left IFOF are involved in alerting. Higher FA in the IFOF predicts better reading scores, and FA in the left IFOF is related to better orthographic processing. In addition, the IFOF plays a crucial role in multimodal semantic processes, including naming and non-verbal semantic associations, constituting a bilateral network, which sustains non-verbal semantic system. Moreover, microstructural properties of the IFOF predict object working memory task performance and therefore underlie nonspatial working memory processing. However, the anatomical features of the IFOF are still a matter of discussion and there is still no consensus regarding the mechanisms and the degree to which anatomical and microstructural properties of this bundle can vary in healthy brains.

78A DTI study by demonstrates the association between DTI metrics in the UF and visual memory task performance. Studies of mild cognitive impairment and psychopathology support a critical role of the UF in higher-order cognitive functions, including attention, spatial memory, and emotion recognition. The involvement of the UF in visual associative learning was found in the DTI study by, who demonstrated a strong positive association between learning rate and microstructural properties of the left UF, suggesting a critical role of the UF in information retrieval. Other DTI studies show strong relations among microstructural characteristics of this WM tract in the left and right hemispheres and auditory-verbal processes, but not visual memory in adults, children, and adolescents. The left and right UF may sustain different neurophysiological processes. As such, suggest that the left UF contributes to rapid learning of conditional visual-visual associations, whereas the right UF may mediate immediate retrieval of these associations.

79Microdissection data on spatial organization of the MdLF point at its role in auditory comprehension as a part of the dorsal auditory stream., found that MdLF, together with the extreme capsule, connects cortical regions involved in comprehension of meaningful compared to non-meaningful sentences. Although the functional role of the MdLF is still unknown, some suggest that its anatomy relates to a role in language. However, electrical stimulation and resection of this fiber tract in the language dominant hemisphere of a patient with brain tumor did not cause language deficits. Further, as evidence by DTI studies, FA in the MdLF, as well as the tract volume, does not display hemispheric asymmetry, as expected for language-related tracts. More research is needed to understand the functional role of this fascinating fiber tract.

80Neurosurgical studies suggest the role of FAT in speech planning and initiation, and it is hypothesized to subserve a link between sentence planning and lexical access. Moreover, FAT was recently identified as a part of a motor language stream involved in speech production. The role of FAT in language can be inferred from its leftward lateralization in right-handed individuals, similar to other language-related fiber systems. Interestingly, intraoperative direct current stimulation of the left FAT leads to shuttering and speech deficits. Damage to this fiber tract leads to verbal fluency, but not grammar deficits in primary progressive aphasia. Notably, DTI studies suggest that individual microstructural characteristics of FAT maintain kinematics and visuomotor processes, and are involved in visually guided hand movements, such as grasping. In older adults, DTI characteristics of FAT, together with the left SLF, predict working memory performance and are hypothesized to be involved in the maintenance, attending, and manipulation of language-related information. Due to limited data on the association between FAT microstructure and cognitive function, the role of this fiber pathway is mainly evidenced from studies of functional role of the cortical regions it connects. As such, the role of the right IFG and pre-SMA/SMA in inhibitory control may indicate the involvement of the FAT connecting these regions in executive functions. There are many questions that remain to be answered on the intricate relation of mental function to structural properties of FAT that link psychology, biology and neuroscience.

81Biological development is associated with maturation of WM pathways which connect distant and proximal brain regions and are critical components of cognitive processing. Our review suggests that myelination follows a complex developmental trajectory that may vary by age, fiber tract and hemisphere. Effects of gender were also identified, although differences may be confounded by methodological factors (e.g., not controlling for brain volume) or social and learning opportunities. Although different studies use various methodological approaches and it is a challenge to aggregate data, future studies should examine overarching pattern across studies using meta-analytical approaches. The study of the individual differences in cerebral WM myelination is very important for developmental biology and neuroscience. Practically, understanding how and when myelination changes and its relation to cognitive performance can inform education practice and clinical interventions.

82IB and MA conceptualized the project and revised and finalized the manuscript. IB wrote the first draft. MA edited versions of the manuscript. Both authors contributed to the article and approved the submitted version.

83The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.