Evolution of white matter tract microstructure across the life span

Hearing loss and its relation to longitudinal changes in white matter microstructure in older adults: The Rotterdam Study

Hearing loss is considered a potentially modifiable risk factor for dementia. The sensory deprivation theory postulates that hearing loss adversely affects cognition in older adults through structural brain changes, but longitudinal studies are scarce. To find evidence for a possible detrimental effect of hearing loss on white matter microstructure, we carried out a longitudinal study in the population-based Rotterdam Study. A total of 1877 participants with a median age at baseline of 56.4 years (IQR: [52.2-60.0]) underwent audiometry and had longitudinal diffusion imaging data available with a mean follow-up of 4.0 years. A lower level of hearing acuity was associated with worse white matter microstructure in the left uncinate fasciculus and superior longitudinal fasciculus at baseline. Poorer hearing acuity was also associated with faster microstructural deterioration over time in the left superior longitudinal fasciculus. The strongest effects were observed for low-frequency hearing thresholds, while the high-frequency thresholds showed the weakest associations. These results suggest that hearing loss may contribute to the age-related decline in brain structure, consistent with the sensory deprivation theory.

Testing retrogenesis and physiological explanations for tract-wise white matter aging: links to developmental order, fibre calibre, and vascularization

To understand the consistently observed spatial distribution of white-matter (WM) aging, developmentally driven theories termed "retrogenesis" have gained traction, positing that the order of WM tract development predicts the order of declines. Regions that develop first are expected to deteriorate the last, i.e. "last-in-first-out". Alternatively, regions which develop most rapidly may also decline most rapidly in aging, or "gains-predict-loss". The validity of such theories remains uncertain, in part due to lack of clarity on the definition of developmental order. Importantly, our recent findings suggest that WM aging is also associated with physiological parameters such as perfusion, which may be linked to fibre metabolic need, which in turn varies with fibre size. Here we address the extent to which the degree of WM aging is determined by development trajectory (i.e. retrogenesis) and/or by physiological state. We obtained microstructural and perfusion measures using data from the Human Connectome Project in Aging (HCP-A), complemented by a meta-analysis involving maps of fibre calibre and macrovascular volume. Our results suggest that (1) while tracts that appear last or finish myelinating first in development display the slowest aging, the pattern of aging is not fully explained by retrogenesis; in fact, time courses of tract emergence and myelination give rise to opposite associations with WM decline; (2) tracts that appear earlier also have higher mean axon calibre and are also associated with lower degrees of WM microstructural aging; (3) such tracts also tend to exhibit relatively sustained CBF with a higher rate of lengthening of the arterial transit times (ATT), suggestive of collateral blood supply. These findings were also sex dependent in a tract-specific manner. Future work will investigate whether these are ultimately influenced by each tract's metabolic demand and the role of macrovascular collateral flow.

Asymmetry of the Frontal Aslant Tract Depends on Handedness

BACKGROUND AND PURPOSE

The human brain displays structural and functional disparities between its hemispheres, with such asymmetry extending to the frontal aslant tract. This plays a role in a variety of cognitive functions, including speech production, language processing, and executive functions. However, the factors influencing the laterality of the frontal aslant tract remain incompletely understood. Handedness is hypothesized to impact frontal aslant tract laterality, given its involvement in both language and motor control. In this study, we aimed to investigate the relationship between handedness and frontal aslant tract lateralization, providing insight into this aspect of brain organization.

MATERIALS AND METHODS

The Automated Tractography Pipeline was used to generate the frontal aslant tract for both right and left hemispheres in a cohort of 720 subjects sourced from the publicly available Human Connectome Project in Aging database. Subsequently, macrostructural and microstructural parameters of the right and left frontal aslant tract were extracted for each individual in the study population. The Edinburgh Handedness Inventory scores were used for the classification of handedness, and a comparative analysis across various handedness groups was performed.

RESULTS

An age-related decline in both macrostructural parameters and microstructural integrity was noted within the studied population. The frontal aslant tract demonstrated a greater volume and larger diameter in male subjects compared with female participants. Additionally, a left-side laterality of the frontal aslant tract was observed within the general population. In the right-handed group, the volume (P < .001), length (P < .001), and diameter (P = .004) of the left frontal aslant tract were found to be higher than those of the right frontal aslant tract. Conversely, in the left-handed group, the volume (P = .040) and diameter (P = .032) of the left frontal aslant tract were lower than those of the right frontal aslant tract. Furthermore, in the right-handed group, the volume and diameter of the frontal aslant tract showed left-sided lateralization, while in the left-handed group, a right-sided lateralization was evident.

CONCLUSIONS

The laterality of the frontal aslant tract appears to differ with handedness. This finding highlights the complex interaction between brain lateralization and handedness, emphasizing the importance of considering handedness as a factor in evaluating brain structure and function.

Prediction of H3K27M Alteration Status in Brainstem Glioma Using Multi-Shell Diffusion MRI Metrics

BACKGROUND

Multi-shell diffusion characteristics may help characterize brainstem gliomas (BSGs) and predict H3K27M status.

PURPOSE

To identify the diffusion characteristics of BSG patients and investigate the predictive values of various diffusion metrics for H3K27M status in BSG.

STUDY TYPE

Prospective.

POPULATION

Eighty-four BSG patients (median age 10.5 years [IQR 6.8-30.0 years]) were included, of whom 56 were pediatric and 28 were adult patients.

FIELD STRENGTH/SEQUENCE

3 T, multi-shell diffusion imaging.

ASSESSMENT

Diffusion kurtosis imaging and neurite orientation dispersion and density imaging analyses were performed. Age, gender, and diffusion metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity, radial diffusivity (RD), mean kurtosis (MK), axial kurtosis (AK), radial kurtosis, intracellular volume fraction (ICVF), orientation dispersion index, and isotropic volume fraction (ISOVF), were compared between H3K27M-altered and wildtype BSG patients.

STATISTICAL TESTS

Chi-square test, Mann-Whitney U test, multivariate analysis of variance (MANOVA), step-wise multivariable logistic regression. P-values <0.05 were considered significant.

RESULTS

82.4% pediatric and 57.1% adult patients carried H3K27M alteration. In the whole group, the H3K27M-altered BSGs demonstrated higher FA, AK and lower RD, ISOVF. The combination of age and median ISOVF showed fair performance for H3K27M prediction (AUC = 0.78). In the pediatric group, H3K27M-altered BSGs showed higher FA, AK, MK, ICVF and lower RD, MD, ISOVF. The combinations of median ISOVF, 5th percentile of FA, median MK and median MD showed excellent predictive power (AUC = 0.91). In the adult group, H3K27M-altered BSGs showed higher ICVF and lower RD, MD. The 75th percentile of RD demonstrated fair performance for H3K27M status prediction (AUC = 0.75).

DATA CONCLUSION

Different alteration patterns of diffusion measures were identified between H3K27M-altered and wildtype BSGs, which collectively had fair to excellent predictive value for H3K27M alteration status, especially in pediatric patients.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 3.

Superagers Resist Typical Age-Related White Matter Structural Changes

Superagers are elderly individuals with the memory ability of people 30 years younger and provide evidence that age-related cognitive decline is not inevitable. In a sample of 64 superagers (mean age, 81.9; 59% women) and 55 typical older adults (mean age, 82.4; 64% women) from the Vallecas Project, we studied, cross-sectionally and longitudinally over 5 years with yearly follow-ups, the global cerebral white matter status as well as region-specific white matter microstructure assessment derived from diffusivity measures. Superagers and typical older adults showed no difference in global white matter health (total white matter volume, Fazekas score, and lesions volume) cross-sectionally or longitudinally. However, analyses of diffusion parameters revealed the better white matter microstructure in superagers than in typical older adults. Cross-sectional differences showed higher fractional anisotropy (FA) in superagers mostly in frontal fibers and lower mean diffusivity (MD) in most white matter tracts, expressed as an anteroposterior gradient with greater group differences in anterior tracts. FA decrease over time is slower in superagers than in typical older adults in all white matter tracts assessed, which is mirrored by MD increases over time being slower in superagers than in typical older adults in all white matter tracts except for the corticospinal tract, the uncinate fasciculus, and the forceps minor. The better preservation of white matter microstructure in superagers relative to typical older adults supports resistance to age-related brain structural changes as a mechanism underpinning the remarkable memory capacity of superagers, while their regional aging pattern is in line with the last-in-first-out hypothesis.

Age-related Differences in Response Inhibition Are Mediated by Frontoparietal White Matter but Not Functional Activity

Healthy older adults often exhibit lower performance but increased functional recruitment of the frontoparietal control network during cognitive control tasks. According to the cortical disconnection hypothesis, age-related changes in the microstructural integrity of white matter may disrupt inter-regional neuronal communication, which in turn can impair behavioral performance. Here, we use fMRI and diffusion-weighted imaging to determine whether age-related differences in white matter microstructure contribute to frontoparietal over-recruitment and behavioral performance during a response inhibition (go/no-go) task in an adult life span sample (n = 145). Older and female participants were slower (go RTs) than younger and male participants, respectively. However, participants across all ages were equally accurate on the no-go trials, suggesting some participants may slow down on go trials to achieve high accuracy on no-go trials. Across the life span, functional recruitment of the frontoparietal network within the left and right hemispheres did not vary as a function of age, nor was it related to white matter fractional anisotropy (FA). In fact, only frontal FA and go RTs jointly mediated the association between age and no-go accuracy. Our results therefore suggest that frontal white matter cortical "disconnection" is an underlying driver of age-related differences in cognitive control, and white matter FA may not fully explain functional task-related activation in the frontoparietal network during the go/no-go task. Our findings add to the literature by demonstrating that white matter may be more important for certain cognitive processes in aging than task-related functional activation.

Brain elastography in aging relates to fluid/solid trendlines

The relatively new tools of brain elastography have established a general trendline for healthy, aging adult humans, whereby the brain's viscoelastic properties 'soften' over many decades. Earlier studies of the aging brain have demonstrated a wide spectrum of changes in morphology and composition towards the later decades of lifespan. This leads to a major question of causal mechanisms: of the many changes documented in structure and composition of the aging brain, which ones drive the long term trendline for viscoelastic properties of grey matter and white matter? The issue is important for illuminating which factors brain elastography is sensitive to, defining its unique role for study of the brain and clinical diagnoses of neurological disease and injury. We address these issues by examining trendlines in aging from our elastography data, also utilizing data from an earlier landmark study of brain composition, and from a biophysics model that captures the multiscale biphasic (fluid/solid) structure of the brain. Taken together, these imply that long term changes in extracellular water in the glymphatic system of the brain along with a decline in the extracellular matrix have a profound effect on the measured viscoelastic properties. Specifically, the trendlines indicate that water tends to replace solid fraction as a function of age, then grey matter stiffness decreases inversely as water fraction squared, whereas white matter stiffness declines inversely as water fraction to the 2/3 power, a behavior consistent with the cylindrical shape of the axons. These unique behaviors point to elastography of the brain as an important macroscopic measure of underlying microscopic structural change, with direct implications for clinical studies of aging, disease, and injury.

The Neurobiology of Life Course Socioeconomic Conditions and Associated Cognitive Performance in Middle to Late Adulthood

Despite major advances, our understanding of the neurobiology of life course socioeconomic conditions is still scarce. This study aimed to provide insight into the pathways linking socioeconomic exposures-household income, last known occupational position, and life course socioeconomic trajectories-with brain microstructure and cognitive performance in middle to late adulthood. We assessed socioeconomic conditions alongside quantitative relaxometry and diffusion-weighted magnetic resonance imaging indicators of brain tissue microstructure and cognitive performance in a sample of community-dwelling men and women (N = 751, aged 50-91 years). We adjusted the applied regression analyses and structural equation models for the linear and nonlinear effects of age, sex, education, cardiovascular risk factors, and the presence of depression, anxiety, and substance use disorders. Individuals from lower-income households showed signs of advanced brain white matter (WM) aging with greater mean diffusivity (MD), lower neurite density, lower myelination, and lower iron content. The association between household income and MD was mediated by neurite density (B = 0.084, p = 0.003) and myelination (B = 0.019, p = 0.009); MD partially mediated the association between household income and cognitive performance (B = 0.017, p < 0.05). Household income moderated the relation between WM microstructure and cognitive performance, such that greater MD, lower myelination, or lower neurite density was only associated with poorer cognitive performance among individuals from lower-income households. Individuals from higher-income households showed preserved cognitive performance even with greater MD, lower myelination, or lower neurite density. These findings provide novel mechanistic insights into the associations between socioeconomic conditions, brain anatomy, and cognitive performance in middle to late adulthood.

The Genomic Intersection of Oligodendrocyte Dynamics in Schizophrenia and Aging Unravels Novel Pathological Mechanisms and Therapeutic Potentials

Schizophrenia is a significant worldwide health concern, affecting over 20 million individuals and contributing to a potential reduction in life expectancy by up to 14.5 years. Despite its profound impact, the precise pathological mechanisms underlying schizophrenia continue to remain enigmatic, with previous research yielding diverse and occasionally conflicting findings. Nonetheless, one consistently observed phenomenon in brain imaging studies of schizophrenia patients is the disruption of white matter, the bundles of myelinated axons that provide connectivity and rapid signalling between brain regions. Myelin is produced by specialised glial cells known as oligodendrocytes, which have been shown to be disrupted in post-mortem analyses of schizophrenia patients. Oligodendrocytes are generated throughout life by a major population of oligodendrocyte progenitor cells (OPC), which are essential for white matter health and plasticity. Notably, a decline in a specific subpopulation of OPC has been identified as a principal factor in oligodendrocyte disruption and white matter loss in the aging brain, suggesting this may also be a factor in schizophrenia. In this review, we analysed genomic databases to pinpoint intersections between aging and schizophrenia and identify shared mechanisms of white matter disruption and cognitive dysfunction.

Polygenic scores for autism are associated with neurite density in adults and children from the general population

Genetic variants linked to autism are thought to change cognition and behaviour by altering the structure and function of the brain. Although a substantial body of literature has identified structural brain differences in autism, it is unknown whether autism-associated common genetic variants are linked to changes in cortical macro- and micro-structure. We investigated this using neuroimaging and genetic data from adults (UK Biobank, N = 31,748) and children (ABCD, N = 4,928). Using polygenic scores and genetic correlations we observe a robust negative association between common variants for autism and a magnetic resonance imaging derived phenotype for neurite density (intracellular volume fraction) in the general population. This result is consistent across both children and adults, in both the cortex and in white matter tracts, and confirmed using polygenic scores and genetic correlations. There were no sex differences in this association. Mendelian randomisation analyses provide no evidence for a causal relationship between autism and intracellular volume fraction, although this should be revisited using better powered instruments. Overall, this study provides evidence for shared common variant genetics between autism and cortical neurite density.

An open relaxation-diffusion MRI dataset in neurosurgical studies

Diffusion MRI (dMRI) is a safe and noninvasive technique that provides insight into the microarchitecture of brain tissue. Relaxation-diffusion MRI (rdMRI) is an extension of traditional dMRI that captures diffusion imaging data at multiple TEs to detect tissue heterogeneity between relaxation and diffusivity. rdMRI has great potential in neurosurgical research including brain tumor grading and treatment response evaluation. However, the lack of available data has limited the exploration of rdMRI in clinical settings. To address this, we are sharing a high-quality rdMRI dataset from 18 neurosurgical patients with different types of lesions, as well as two healthy individuals as controls. The rdMRI data was acquired using 7 TEs, where at each TE multi-shell dMRI with high spatial and angular resolutions is obtained at each TE. Each rdMRI scan underwent thorough artifact and distortion corrections using a specially designed processing pipeline. The dataset's quality was assessed using standard practices, including quality control and assurance. This resource is a valuable addition to neurosurgical studies, and all data are openly accessible.

Impact of corpus callosum integrity on functional interhemispheric connectivity and cognition in healthy subjects

To examine the corpus callosum's (CC) integrity in terms of fractional anisotropy (FA) and how it affects resting-state hemispheric connectivity (rs-IHC) and cognitive function in healthy individuals. Sixty-eight healthy individuals were recruited for the study. The global FA (gFA) and FA values of each CC tract (forceps minor, body, tapetum, and forceps major) were evaluated using diffusion-weighted imaging (DWI) sequences. The homotopic functional connectivity technique was used to quantify the effects of FA in the CC tracts on bilateral functional connectivity, including the confounding effect of gFA. Brain regions with higher or lower rs-IHC were identified using the threshold-free cluster enhancement family-wise error-corrected p-value of 0.05. The null hypothesis was rejected if the p-value was ≤ 0.05 for the nonparametric partial correlation technique. Several clusters of increased rs-IHC were identified in relation to the FA of individual CC tracts, each with a unique topographic distribution and extension. Only forceps minor FA values correlated with cognitive scores. The integrity of CC influences rs-IHC differently in healthy subjects. Specifically, forceps minor anisotropy impacts rs-IHC and cognition more than other CC tracts do.

Age-related differences in structural and resting-state functional brain network organization across the adult lifespan: A cross-sectional study

We investigated age-related trends in the topology and hierarchical organization of brain structural and functional networks using diffusion-weighted imaging and resting-state fMRI data from a large cohort of healthy aging adults. At the cross-modal level, we explored age-related patterns in the RC involvement of different functional subsystems using a high-resolution functional parcellation. We further assessed age-related differences in the structure-function coupling as well as the network vulnerability to damage to rich club connectivity. Regardless of age, the structural and functional brain networks exhibited a rich club organization and small-world topology. In older individuals, we observed reduced integration and segregation within the frontal-occipital regions and the cerebellum along the brain's medial axis. Additionally, functional brain networks displayed decreased integration and increased segregation in the prefrontal, centrotemporal, and occipital regions, and the cerebellum. In older subjects, structural networks also exhibited decreased within-network and increased between-network RC connectivity. Furthermore, both within-network and between-network RC connectivity decreased in functional networks with age. An age-related decline in structure-function coupling was observed within sensory-motor, cognitive, and subcortical networks. The structural network exhibited greater vulnerability to damage to RC connectivity within the language-auditory, visual, and subcortical networks. Similarly, for functional networks, increased vulnerability was observed with damage to RC connectivity in the cerebellum, language-auditory, and sensory-motor networks. Overall, the network vulnerability decreased significantly in subjects older than 70 in both networks. Our findings underscore significant age-related differences in both brain functional and structural RC connectivity, with distinct patterns observed across the adult lifespan.

Evaluation of tractography-based myelin-weighted connectivity across the lifespan

Introduction

Recent studies showed that the myelin of the brain changes in the life span, and demyelination contributes to the loss of brain plasticity during normal aging. Diffusion-weighted magnetic resonance imaging (dMRI) allows studying brain connectivity in vivo by mapping axons in white matter with tractography algorithms. However, dMRI does not provide insight into myelin; thus, combining tractography with myelin-sensitive maps is necessary to investigate myelin-weighted brain connectivity. Tractometry is designated for this purpose, but it suffers from some serious limitations. Our study assessed the effectiveness of the recently proposed Myelin Streamlines Decomposition (MySD) method in estimating myelin-weighted connectomes and its capacity to detect changes in myelin network architecture during the process of normal aging. This approach opens up new possibilities compared to traditional Tractometry.

Methods

In a group of 85 healthy controls aged between 18 and 68 years, we estimated myelin-weighted connectomes using Tractometry and MySD, and compared their modulation with age by means of three well-known global network metrics.

Results

Following the literature, our results show that myelin development continues until brain maturation (40 years old), after which degeneration begins. In particular, mean connectivity strength and efficiency show an increasing trend up to 40 years, after which the process reverses. Both Tractometry and MySD are sensitive to these changes, but MySD turned out to be more accurate.

Conclusion

After regressing the known predictors, MySD results in lower residual error, indicating that MySD provides more accurate estimates of myelin-weighted connectivity than Tractometry.

Development of white matter fiber covariance networks supports executive function in youth

During adolescence, the brain undergoes extensive changes in white matter structure that support cognition. Data-driven approaches applied to cortical surface properties have led the field to understand brain development as a spatially and temporally coordinated mechanism that follows hierarchically organized gradients of change. Although white matter development also appears asynchronous, previous studies have relied largely on anatomical tract-based atlases, precluding a direct assessment of how white matter structure is spatially and temporally coordinated. Harnessing advances in diffusion modeling and machine learning, we identified 14 data-driven patterns of covarying white matter structure in a large sample of youth. Fiber covariance networks aligned with known major tracts, while also capturing distinct patterns of spatial covariance across distributed white matter locations. Most networks showed age-related increases in fiber network properties, which were also related to developmental changes in executive function. This study delineates data-driven patterns of white matter development that support cognition.

Comparing neuromotor functions in 45- and 65-year-old adults with 18-year-old adolescents

Aim

This cross-sectional analysis investigates how neuromotor functions of two independent cohorts of approximately 45- and 65-year-old individuals are different from 18-year-old adolescents using the Zurich Neuromotor Assessment-2 (ZNA-2).

Methods

A total of 186 individuals of the Zurich Longitudinal Studies (ZLS) born in the 1950s (mean age 65.1 years, SD = 1.2 year, range of ages 59.0-67.5 years, n = 151, 82 males) and 1970s (mean age 43.6 years, SD = 1.3 year, range of ages 40.8-46.6 years, n = 35, 16 males) were tested with the ZNA-2 on 14 motor tasks combined in 5 motor components: fine motor, pure motor, balance, gross motor, and associated movements. Motor performance measures were converted into standard deviation scores (SDSs) using the normative data for 18-year-old individuals as reference.

Results

The motor performance of the 45-year-old individuals was remarkably similar to that of the 18-year-olds (SDS from -0.22 to 0.25) apart from associated movements (-0.49 SDS). The 65-year-olds showed lower performance than the 18-year-olds in all components of the ZNA-2, with the smallest difference observed for associated movements (-0.67 SDS) and the largest for gross motor skills (-2.29 SDS). Higher body mass index (BMI) was associated with better performance on gross motor skills for 45-year-olds but with worse performance for 65-year-olds. More educational years had positive effects on gross motor skills for both ages.

Interpretation

With the exception of associated movements, neuromotor functions as measured with the ZNA-2 are very similar in 45- and 18-year-olds. In contrast, at age 65 years, all neuromotor components show significantly lower function than the norm population at 18 years. Some evidence was found for the last-in-first-out hypothesis: the functions that developed later during adolescence, associated movements and gross motor skills, were the most vulnerable to age-related decline.

Traveling Subject-Informed Harmonization Increases Reliability of Brain Diffusion Tensor and Neurite Mapping

Diffusion-weighted magnetic resonance imaging (dMRI) of brain has helped elucidate the microstructural changes of psychiatric and neurodegenerative disorders. Inconsistency between MRI models has hampered clinical application of dMRI-based metrics. Using harmonized dMRI data of 300 scans from 69 traveling subjects (TS) scanning the same individuals at multiple conditions with 13 MRI models and 2 protocols, the widely-used metrics such as diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) were evaluated before and after harmonization with a combined association test (ComBat) or TS-based general linear model (TS-GLM). Results showed that both ComBat and TS-GLM significantly reduced the effects of the MRI site, model, and protocol for diffusion metrics while maintaining the intersubject biological effects. The harmonization power of TS-GLM based on TS data model is more powerful than that of ComBat. In conclusion, our research demonstrated that although ComBat and TS-GLM harmonization approaches were effective at reducing the scanner effects of the site, model, and protocol for DTI and NODDI metrics in WM, they exhibited high retainability of biological effects. Therefore, we suggest that, after harmonizing DTI and NODDI metrics, a multisite study with large cohorts can accurately detect small pathological changes by retaining pathological effects.

Single-subject electroencephalography measurement of interhemispheric transfer time for the in-vivo estimation of axonal morphology

Assessing axonal morphology in vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to estimate the morphology of axonal fibers from the combination of magnetic resonance imaging (MRI) data and electroencephalography (EEG) measures of the interhemispheric transfer time (IHTT). In the original study, the IHTT measures were computed from EEG data averaged across a group, leading to bias of the axonal morphology estimates. Here, we seek to estimate axonal morphology from individual measures of IHTT, obtained from EEG data acquired in a visual evoked potential experiment. Subject-specific IHTTs are computed in a data-driven framework with minimal a priori constraints, based on the maximal peak of neural responses to visual stimuli within periods of statistically significant evoked activity in the inverse solution space. The subject-specific IHTT estimates ranged from 8 to 29 ms except for one participant and the between-session variability was comparable to between-subject variability. The mean radius of the axonal radius distribution, computed from the IHTT estimates and the MRI data, ranged from 0 to 1.09 μm across subjects. The change in axonal g-ratio with axonal radius ranged from 0.62 to 0.81 μm-α . The single-subject measurement of the IHTT yields estimates of axonal morphology that are consistent with histological values. However, improvement of the repeatability of the IHTT estimates is required to improve the specificity of the single-subject axonal morphology estimates.

White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan

Characterizing how, when and where the human brain changes across the lifespan is fundamental to our understanding of developmental processes of childhood and adolescence, degenerative processes of aging, and divergence from normal patterns in disease and disorders. We aimed to provide detailed descriptions of white matter pathways across the lifespan by thoroughly characterizing white matter microstructure, white matter macrostructure, and morphology of the cortex associated with white matter pathways. We analyzed 4 large, high-quality, publicly-available datasets comprising 2789 total imaging sessions, and participants ranging from 0 to 100 years old, using advanced tractography and diffusion modeling. We first find that all microstructural, macrostructural, and cortical features of white matter bundles show unique lifespan trajectories, with rates and timing of development and degradation that vary across pathways - describing differences between types of pathways and locations in the brain, and developmental milestones of maturation of each feature. Second, we show cross-sectional relationships between different features that may help elucidate biological changes occurring during different stages of the lifespan. Third, we show unique trajectories of age-associations across features. Finally, we find that age associations during development are strongly related to those during aging. Overall, this study reports normative data for several features of white matter pathways of the human brain that will be useful for studying normal and abnormal white matter development and degeneration.

White matter microstructural integrity continues to develop from adolescence to young adulthood in mice and humans: Same phenotype, different mechanism

As direct evaluation of a mouse model of human neurodevelopment, adolescent and young adult mice and humans underwent MR diffusion tensor imaging to quantify age-related differences in microstructural integrity of brain white matter fibers. Fractional anisotropy (FA) was greater in older than younger mice and humans. Despite the cross-species commonality, the underlying developmental mechanism differed: whereas evidence for greater axonal extension contributed to higher FA in older mice, evidence for continuing myelination contributed to higher FA in human adolescent development. These differences occurred in the context of species distinctions in overall brain growth: whereas the continued growth of the brain and skull in the murine model can accommodate volume expansion into adulthood, human white matter volume and myelination continue growth into adulthood within a fixed intracranial volume. Appreciation of the similarities and differences in developmental mechanism can enhance the utility of animal models of brain white matter structure, function, and response to exogenous manipulation.

Metabolic syndrome and adiposity: Risk factors for decreased myelin in cognitively healthy adults

Metabolic syndrome (MetS) is a cluster of conditions that affects ∼25% of the global population, including excess adiposity, hyperglycemia, dyslipidemia, and elevated blood pressure. MetS is one of major risk factors not only for chronic diseases, but also for dementia and cognitive dysfunction, although the underlying mechanisms remain poorly understood. White matter is of particular interest in the context of MetS due to the metabolic vulnerability of myelin maintenance, and the accumulating evidence for the importance of the white matter in the pathophysiology of dementia. Therefore, we investigated the associations of MetS risk score and adiposity (combined body mass index and waist circumference) with myelin water fraction measured with myelin water imaging. In 90 cognitively and neurologically healthy adults (20-79 years), we found that both high MetS risk score and adiposity were correlated with lower myelin water fraction in late-myelinating prefrontal and associative fibers, controlling for age, sex, race, ethnicity, education and income. Our findings call for randomized clinical trials to establish causality between MetS, adiposity, and myelin content, and to explore the potential of weight loss and visceral adiposity reduction as means to support maintenance of myelin integrity throughout adulthood, which could open new avenues for prevention or treatment of cognitive decline and dementia.

Learning Spectral Fractional Anisotropy and Mean Diffusivity Features as Neuroimaging Biomarkers for Tracking White Matter Integrity Changes in Myotonic Dystrophy Type 1 Patients using Deep Convolutional Neural Networks

Myotonic dystrophy type 1 (DM1) is a genetic neuromuscular progressive multisystem disease that results in a broad spectrum of clinical central nervous system (CNS) involvement, including problems with memory, attention, executive functioning, and social cognition. Fractional anisotropy and mean diffusivity along-tract data calculated using diffusion tensor imaging techniques play a vital role in assessing white matter microstructural changes associated with neurodegeneration caused by DM1. In this work, a novel spectrogram-based deep learning method is proposed to characterize white matter network alterations in DM1 with the goal of building a deep learning model as neuroimaging biomarkers of DM1. The proposed method is evaluated on fractional anisotropies and mean diffusivities along-tract data calculated for 25 major white matter tracts of 46 DM1 patients and 96 unaffected controls. The evaluation data consists of a total of 7100 spectrogram images. The model achieved 91% accuracy in identifying DM1, a significant improvement compared to previous methods.Clinical relevance- Clinical care of DM1 is particularly challenging due to DM1 multisystem involvement and the disease variability. Patients with DM1 often experience neurological and psychological symptoms, such as excessive sleepiness and apathy, that greatly impact their quality of life. Some of DM1 CNS symptoms may be responsive to treatment. The goal of this research is to gain a deeper understanding of the impact of DM1 on the CNS and to develop a deep learning model that can serve as a biomarker for the disease, with the potential to be used in future clinical trials as an outcome measure.

New horizons in emotional well-being and brain aging: Potential lessons from cross-species research

Emotional wellbeing (EWB) is a multi-faceted concept of immediate relevance to human health. NIH recently initiated a series of research networks to advance understanding of EWB. Our network (NEW Brain Aging) focuses on mechanistic understanding of EWB in relation to brain aging. Here, by synthesizing the literature on emotional processing and the underlying brain circuit mechanisms in human and non-human animals, we propose a reactivity and reappraisal model for understanding EWB and its age-related changes. This model emphasizes the dynamic interactions between affective stimuli, behavioral/physiological responses, brain emotional states, and subjective feelings. It also aims to integrate the unique emotional processes involved in explaining EWB in aging humans with the emerging mechanistic insight of topologically conserved emotional brain networks from cross-species studies. We also highlight the research opportunities and challenges in EWB and brain aging research and the potential application of the model in addressing these issues.

Atypical developmental trajectories of white matter microstructure in prenatal alcohol exposure: Preliminary evidence from neurite orientation dispersion and density imaging

Introduction

Fetal alcohol spectrum disorder (FASD), a life-long condition resulting from prenatal alcohol exposure (PAE), is associated with structural brain anomalies and neurobehavioral differences. Evidence from longitudinal neuroimaging suggest trajectories of white matter microstructure maturation are atypical in PAE. We aimed to further characterize longitudinal trajectories of developmental white matter microstructure change in children and adolescents with PAE compared to typically-developing Controls using diffusion-weighted Neurite Orientation Dispersion and Density Imaging (NODDI).

Materials and methods

Participants: Youth with PAE (n = 34) and typically-developing Controls (n = 31) ages 8-17 years at enrollment. Participants underwent formal evaluation of growth and facial dysmorphology. Participants also completed two study visits (17 months apart on average), both of which involved cognitive testing and an MRI scan (data collected on a Siemens Prisma 3 T scanner). Age-related changes in the orientation dispersion index (ODI) and the neurite density index (NDI) were examined across five corpus callosum (CC) regions defined by tractography.

Results

While linear trajectories suggested similar overall microstructural integrity in PAE and Controls, analyses of symmetrized percent change (SPC) indicated group differences in the timing and magnitude of age-related increases in ODI (indexing the bending and fanning of axons) in the central region of the CC, with PAE participants demonstrating atypically steep increases in dispersion with age compared to Controls. Participants with PAE also demonstrated greater increases in ODI in the mid posterior CC (trend-level group difference). In addition, SPC in ODI and NDI was differentially correlated with executive function performance for PAE participants and Controls, suggesting an atypical relationship between white matter microstructure maturation and cognitive function in PAE.

Discussion

Preliminary findings suggest subtle atypicality in the timing and magnitude of age-related white matter microstructure maturation in PAE compared to typically-developing Controls. These findings add to the existing literature on neurodevelopmental trajectories in PAE and suggest that advanced biophysical diffusion modeling (NODDI) may be sensitive to biologically-meaningful microstructural changes in the CC that are disrupted by PAE. Findings of atypical brain maturation-behavior relationships in PAE highlight the need for further study. Further longitudinal research aimed at characterizing white matter neurodevelopmental trajectories in PAE will be important.

Symmetric data-driven fusion of diffusion tensor MRI: Age differences in white matter

In the past 20 years, white matter (WM) microstructure has been studied predominantly using diffusion tensor imaging (DTI). Decreases in fractional anisotropy (FA) and increases in mean (MD) and radial diffusivity (RD) have been consistently reported in healthy aging and neurodegenerative diseases. To date, DTI parameters have been studied individually (e.g., only FA) and separately (i.e., without using the joint information across them). This approach gives limited insights into WM pathology, increases the number of multiple comparisons, and yields inconsistent correlations with cognition. To take full advantage of the information in a DTI dataset, we present the first application of symmetric fusion to study healthy aging WM. This data-driven approach allows simultaneous examination of age differences in all four DTI parameters. We used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) in cognitively healthy adults (age 20-33, n = 51 and age 60-79, n = 170). Four-way mCCA + jICA yielded one high-stability modality-shared component with co-variant patterns of age differences in RD and AD in the corpus callosum, internal capsule, and prefrontal WM. The mixing coefficients (or loading parameters) showed correlations with processing speed and fluid abilities that were not detected by unimodal analyses. In sum, mCCA + jICA allows data-driven identification of cognitively relevant multimodal components within the WM. The presented method should be further extended to clinical samples and other MR techniques (e.g., myelin water imaging) to test the potential of mCCA+jICA to discriminate between different WM disease etiologies and improve the diagnostic classification of WM diseases.

Temporal trajectories of normal myelination and axonal development assessed by quantitative macromolecular and diffusion MRI: Ultrastructural and immunochemical validation in a rabbit model

INTRODUCTION

Quantitative and non-invasive measures of brain myelination and maturation during development are of great importance to both clinical and translational research communities. While the metrics derived from diffusion tensor imaging, are sensitive to developmental changes and some pathologies, they remain difficult to relate to the actual microstructure of the brain tissue. The advent of advanced model-based microstructural metrics requires histological validation. The purpose of the study was to validate novel, model-based MRI techniques, such as macromolecular proton fraction mapping (MPF) and neurite orientation and dispersion indexing (NODDI), against histologically derived indexes of myelination and microstructural maturation at various stages of development.

METHODS

New Zealand White rabbit kits underwent serial in-vivo MRI examination at postnatal days 1, 5, 11, 18, and 25, and as adults. Multi-shell, diffusion-weighted experiments were processed to fit NODDI model to obtain estimates, intracellular volume fraction (ICVF) and orientation dispersion index (ODI). Macromolecular proton fraction (MPF) maps were obtained from three source (MT-, PD-, and T1-weighted) images. After MRI sessions, a subset of animals was euthanized and regional samples of gray and white matter were taken for western blot analysis, to determine myelin basic protein (MBP), and electron microscopy, to estimate axonal, myelin fractions and g-ratio.

RESULTS

MPF of white matter regions showed a period of fast growth between P5 and P11 in the internal capsule, with a later onset in the corpus callosum. This MPF trajectory was in agreement with levels of myelination in the corresponding brain region, as assessed by western blot and electron microscopy. In the cortex, the greatest increase of MPF occurred between P18 and P26. In contrast, myelin, according to MBP western blot, saw the largest hike between P5 and P11 in the sensorimotor cortex and between P11 and P18 in the frontal cortex, which then seemingly plateaued after P11 and P18 respectively. G-ratio by MRI markers decreased with age in the white matter. However, electron microscopy suggest a relatively stable g-ratio throughout development.

CONCLUSION

Developmental trajectories of MPF accurately reflected regional differences of myelination rate in different cortical regions and white matter tracts. MRI-derived estimation of g-ratio was inaccurate during early development, likely due to the overestimation of axonal volume fraction by NODDI due to the presence of a large proportion of unmyelinated axons.

Topography of associations between cardiovascular risk factors and myelin loss in the ageing human brain

Our knowledge of the mechanisms underlying the vulnerability of the brain's white matter microstructure to cardiovascular risk factors (CVRFs) is still limited. We used a quantitative magnetic resonance imaging (MRI) protocol in a single centre setting to investigate the cross-sectional association between CVRFs and brain tissue properties of white matter tracts in a large community-dwelling cohort (n = 1104, age range 46-87 years). Arterial hypertension was associated with lower myelin and axonal density MRI indices, paralleled by higher extracellular water content. Obesity showed similar associations, though with myelin difference only in male participants. Associations between CVRFs and white matter microstructure were observed predominantly in limbic and prefrontal tracts. Additional genetic, lifestyle and psychiatric factors did not modulate these results, but moderate-to-vigorous physical activity was linked to higher myelin content independently of CVRFs. Our findings complement previously described CVRF-related changes in brain water diffusion properties pointing towards myelin loss and neuroinflammation rather than neurodegeneration.

Submillimeter T1 atlas for subject-specific abnormality detection at 7T

PURPOSE

Studies at 3T have shown that T₁ relaxometry enables characterization of brain tissues at the single-subject level by comparing individual physical properties to a normative atlas. In this work, an atlas of normative T₁ values at 7T is introduced with 0.6 mm isotropic resolution and its clinical potential is explored in comparison to 3T.

METHODS

T₁ maps were acquired in two separate healthy cohorts scanned at 3T and 7T. Using transfer learning, a template-based brain segmentation algorithm was adapted to ultra-high field imaging data. After segmenting brain tissues, volumes were normalized into a common space, and an atlas of normative T₁ values was established by modeling the T₁ inter-subject variability. A method for single-subject comparisons restricted to white matter and subcortical structures was developed by computing Z-scores. The comparison was applied to eight patients scanned at both field strengths for proof of concept.

RESULTS

The proposed method for morphometry delivered segmentation masks without statistically significant differences from those derived with the original pipeline at 3T and achieved accurate segmentation at 7T. The established normative atlas allowed characterizing tissue alterations in single-subject comparisons at 7T, and showed greater anatomical details compared with 3T results.

CONCLUSION

A high-resolution quantitative atlas with an adapted pipeline was introduced and validated. Several case studies on different clinical conditions showed the feasibility, potential and limitations of high-resolution single-subject comparisons based on quantitative MRI atlases. This method in conjunction with 7T higher resolution broadens the range of potential applications of quantitative MRI in clinical practice.

Morphometric dis-similarity between cortical and subcortical areas underlies cognitive function and psychiatric symptomatology: a preadolescence study from ABCD

Preadolescence is a critical period characterized by dramatic morphological changes and accelerated cortico-subcortical development. Moreover, the coordinated development of cortical and subcortical regions underlies the emerging cognitive functions during this period. Deviations in this maturational coordination may underlie various psychiatric disorders that begin during preadolescence, but to date these deviations remain largely uncharted. We constructed a comprehensive whole-brain morphometric similarity network (MSN) from 17 neuroimaging modalities in a large preadolescence sample (N = 8908) from Adolescent Brain Cognitive Development (ABCD) study and investigated its association with 10 cognitive subscales and 27 psychiatric subscales or diagnoses. Based on the MSNs, each brain was clustered into five modules with distinct cytoarchitecture and evolutionary relevance. While morphometric correlation was positive within modules, it was negative between modules, especially between isocortical and paralimbic/subcortical modules; this developmental dissimilarity was genetically linked to synapse and neurogenesis. The cortico-subcortical dissimilarity becomes more pronounced longitudinally in healthy children, reflecting developmental differentiation of segregated cytoarchitectonic areas. Higher cortico-subcortical dissimilarity (between the isocortical and paralimbic/subcortical modules) were related to better cognitive performance. In comparison, children with poor modular differentiation between cortex and subcortex displayed higher burden of externalizing and internalizing symptoms. These results highlighted cortical-subcortical morphometric dissimilarity as a dynamic maturational marker of cognitive and psychiatric status during the preadolescent stage and provided insights into brain development.

Development of White Matter Fiber Covariance Networks Supports Executive Function in Youth

The white matter architecture of the human brain undergoes substantial development throughout childhood and adolescence, allowing for more efficient signaling between brain regions that support executive function. Increasingly, the field understands grey matter development as a spatially and temporally coordinated mechanism that follows hierarchically organized gradients of change. While white matter development also appears asynchronous, previous studies have largely relied on anatomical atlases to characterize white matter tracts, precluding a direct assessment of how white matter structure is spatially and temporally coordinated. Here, we leveraged advances in diffusion modeling and unsupervised machine learning to delineate white matter fiber covariance networks comprised of structurally similar areas of white matter in a cross-sectional sample of 939 youth aged 8-22 years. We then evaluated associations between fiber covariance network structural properties with both age and executive function using generalized additive models. The identified fiber covariance networks aligned with the known architecture of white matter while simultaneously capturing novel spatial patterns of coordinated maturation. Fiber covariance networks showed heterochronous increases in fiber density and cross section that generally followed hierarchically organized temporal patterns of cortical development, with the greatest increases in unimodal sensorimotor networks and the most prolonged increases in superior and anterior transmodal networks. Notably, we found that executive function was associated with structural features of limbic and association networks. Taken together, this study delineates data-driven patterns of white matter network development that support cognition and align with major axes of brain maturation.

Frontostriatal and limbic contributions to cognitive decline in Parkinson's disease

BACKGROUND AND PURPOSE

The circuitry underlying heterogenous cognitive profiles in Parkinson's disease (PD) remains unclear. The purpose of this study is to investigate whether structural changes in frontostriatal and limbic pathways contribute to different cognitive trajectories in PD.

METHODS

We obtained clinical and multimodal MRI data from 120 control and 122 PD subjects without dementia or severe motor disability. T1/T2-weighted images estimated volume, and diffusion imaging evaluated fractional anisotropy (FA) of frontostriatal (striatum and frontostriatal white matter [FSWM]) and limbic (hippocampus and fornix) structures. Montreal Cognitive Assessment (MoCA) gauged total and domain-specific (attention/executive and memory) cognitive function. Linear mixed-effects models were used to compare MRI and cognitive progression over 4.5 years between controls and PD and evaluate associations between baseline MRI and cognitive changes in PD.

RESULTS

At baseline, control and PD groups were comparable, except PD participants had smaller striatal volume (p < 0.001). Longitudinally, PD showed faster decline in hippocampal volume, FSWM FA, and fornix FA (ps < .016), but not striatal volume (p = .218). Total and domain-specific MoCA scores declined faster in PD (ps < .030). In PD, lower baseline hippocampal volume (p = .005) and fornix FA (p = .032), but not striatal volume (p = .662) or FSWM FA (p = .143), were associated with faster total MoCA decline. Baseline frontostriatal metrics of striatal volume and FSWM FA were associated with faster attention/executive decline (p < .038), whereas lower baseline hippocampal volume was associated with faster memory decline (p = .005).

CONCLUSION

In PD, frontostriatal structural metrics are associated with attention/executive tasks, whereas limbic changes correlated with faster global cognitive decline, particularly in memory tasks.

Patterns of risk-Using machine learning and structural neuroimaging to identify pedophilic offenders

Background

Child sexual abuse (CSA) has become a focal point for lawmakers, law enforcement, and mental health professionals. With high prevalence rates around the world and far-reaching, often chronic, individual, and societal implications, CSA and its leading risk factor, pedophilia, have been well investigated. This has led to a wide range of clinical tools and actuarial instruments for diagnosis and risk assessment regarding CSA. However, the neurobiological underpinnings of pedosexual behavior, specifically regarding hands-on pedophilic offenders (PO), remain elusive. Such biomarkers for PO individuals could potentially improve the early detection of high-risk PO individuals and enhance efforts to prevent future CSA.

Aim

To use machine learning and MRI data to identify PO individuals.

Methods

From a single-center male cohort of 14 PO individuals and 15 matched healthy control (HC) individuals, we acquired diffusion tensor imaging data (anisotropy, diffusivity, and fiber tracking) in literature-based regions of interest (prefrontal cortex, anterior cingulate cortex, amygdala, and corpus callosum). We trained a linear support vector machine to discriminate between PO and HC individuals using these WM microstructure data. Post hoc, we investigated the PO model decision scores with respect to sociodemographic (age, education, and IQ) and forensic characteristics (psychopathy, sexual deviance, and future risk of sexual violence) in the PO subpopulation. We assessed model specificity in an external cohort of 53 HC individuals.

Results

The classifier discriminated PO from HC individuals with a balanced accuracy of 75.5% (sensitivity = 64.3%, specificity = 86.7%, P ₅₀₀₀ = 0.018) and an out-of-sample specificity to correctly identify HC individuals of 94.3%. The predictive brain pattern contained bilateral fractional anisotropy in the anterior cingulate cortex, diffusivity in the left amygdala, and structural prefrontal cortex-amygdala connectivity in both hemispheres. This brain pattern was associated with the number of previous child victims, the current stance on sexuality, and the professionally assessed risk of future sexual violent reoffending.

Conclusion

Aberrant white matter microstructure in the prefronto-temporo-limbic circuit could be a potential neurobiological correlate for PO individuals at high-risk of reoffending with CSA. Although preliminary and exploratory at this point, our findings highlight the general potential of MRI-based biomarkers and particularly WM microstructure patterns for future CSA risk assessment and preventive efforts.

Neurite Orientation Dispersion and Density Imaging in Psychiatric Disorders: A Systematic Literature Review and a Technical Note

While major psychiatric disorders lack signature diagnostic neuropathologies akin to dementias, classic postmortem studies have established microstructural involvement, i.e., cellular changes in neurons and glia, as a key pathophysiological finding. Advanced magnetic resonance imaging techniques allow mapping of cellular tissue architecture and microstructural abnormalities in vivo, which holds promise for advancing our understanding of the pathophysiology underlying psychiatric disorders. Here, we performed a systematic review of case-control studies using neurite orientation dispersion and density imaging (NODDI) to assess brain microstructure in psychiatric disorders and a selective review of technical considerations in NODDI. Of the 584 potentially relevant articles, 18 studies met the criteria to be included in this systematic review. We found a general theme of abnormal gray and white matter microstructure across the diagnostic spectrum. We also noted significant variability in patterns of neurite density and fiber orientation within and across diagnostic groups, as well as associations between brain microstructure and phenotypical variables. NODDI has been successfully used to detect subtle microstructure abnormalities in patients with psychiatric disorders. Given that NODDI indices may provide a more direct link to pathophysiological processes, this method may not only contribute to advancing our mechanistic understanding of disease processes, it may also be well positioned for next-generation biomarker development studies.

Frontal grey matter microstructure is associated with sleep slow waves characteristics in late midlife

STUDY OBJECTIVES

The ability to generate slow waves (SW) during non-rapid eye movement (NREM) sleep decreases as early as the 5th decade of life, predominantly over frontal regions. This decrease may concern prominently SW characterized by a fast switch from hyperpolarized to depolarized, or down-to-up, state. Yet, the relationship between these fast and slow switcher SW and cerebral microstructure in ageing is not established.

METHODS

We recorded habitual sleep under EEG in 99 healthy late midlife individuals (mean age = 59.3 ± 5.3 years; 68 women) and extracted SW parameters (density, amplitude, frequency) for all SW as well as according to their switcher type (slow vs. fast). We further used neurite orientation dispersion and density imaging (NODDI) to assess microstructural integrity over a frontal grey matter region of interest (ROI).

RESULTS

In statistical models adjusted for age, sex, and sleep duration, we found that a lower SW density, particularly for fast switcher SW, was associated with a reduced orientation dispersion of neurites in the frontal ROI (p = 0.018, R2β* = 0.06). In addition, overall SW frequency was positively associated with neurite density (p = 0.03, R2β* = 0.05). By contrast, we found no significant relationships between SW amplitude and NODDI metrics.

CONCLUSIONS

Our findings suggest that the complexity of neurite organization contributes specifically to the rate of fast switcher SW occurrence in healthy middle-aged individuals, corroborating slow and fast switcher SW as distinct types of SW. They further suggest that the density of frontal neurites plays a key role for neural synchronization during sleep.

TRIAL REGISTRATION NUMBER

EudraCT 2016-001436-35.

Surface-based tracking for short association fibre tractography

It is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in the neuroimaging literature. Some of the challenges pertinent to the mapping of SAF include their variable anatomical course and proximity to the cortical mantle, leading to partial volume effects and potentially affecting streamline trajectory estimation. This work considers the impact of seeding and filtering strategies and choice of scanner, acquisition, data resampling to propose a whole-brain, surface-based short (≤30-40 mm) SAF tractography approach. The framework is shown to produce longer streamlines with a predilection for connecting gyri as well as high cortical coverage. We further demonstrate that certain areas of subcortical white matter become disproportionally underrepresented in diffusion-weighted MRI data with lower angular and spatial resolution and weaker diffusion weighting; however, collecting data with stronger gradients than are usually available clinically has minimal impact, making our framework translatable to data collected on commonly available hardware. Finally, the tractograms are examined using voxel- and surface-based measures of consistency, demonstrating moderate reliability, low repeatability and high between-subject variability, urging caution when streamline count-based analyses of SAF are performed.

An accelerated degeneration of white matter microstructure and networks in the nondemented old-old

The nondemented old-old over the age of 80 comprise a rapidly increasing population group; they can be regarded as exemplars of successful aging. However, our current understanding of successful aging in advanced age and its neural underpinnings is limited. In this study, we measured the microstructural and network-based topological properties of brain white matter using diffusion-weighted imaging scans of 419 community-dwelling nondemented older participants. The participants were further divided into 230 young-old (between 72 and 79, mean = 76.25 ± 2.00) and 219 old-old (between 80 and 92, mean = 83.98 ± 2.97). Results showed that white matter connectivity in microstructure and brain networks significantly declined with increased age and that the declined rates were faster in the old-old compared with young-old. Mediation models indicated that cognitive decline was in part through the age effect on the white matter connectivity in the old-old but not in the young-old. Machine learning predictive models further supported the crucial role of declines in white matter connectivity as a neural substrate of cognitive aging in the nondemented older population. Our findings shed new light on white matter connectivity in the nondemented aging brains and may contribute to uncovering the neural substrates of successful brain aging.

Bridging cognition and action: executive functioning mediates the relationship between white matter fiber density and complex motor abilities in older adults

Aging may be associated with motor decline that is attributed to deteriorating white matter microstructure of the corpus callosum (CC), among other brain-related factors. Similar to motor functioning, executive functioning (EF) typically declines during aging, with age-associated changes in EF likewise being linked to altered white matter connectivity in the CC. Given that both motor and executive functions rely on white matter connectivity via the CC, and that bimanual control is thought to rely on EF, the question arises whether EF can at least party account for the proposed link between CC-connectivity and motor control in older adults. To address this, diffusion magnetic resonance imaging data were obtained from 84 older adults. A fiber-specific approach was used to obtain fiber density (FD), fiber cross-section (FC), and a combination of both metrics in eight transcallosal white matter tracts. Motor control was assessed using a bimanual coordination task. EF was determined by a domain-general latent EF-factor extracted from multiple EF tasks, based on a comprehensive test battery. FD of transcallosal prefrontal fibers was associated with cognitive and motor performance. EF partly accounted for the relationship between FD of prefrontal transcallosal pathways and motor control. Our results underscore the multidimensional interrelations between callosal white matter connectivity (especially in prefrontal brain regions), EF across multiple domains, and motor control in the older population. They also highlight the importance of considering EF when investigating brain-motor behavior associations in older adults.

CYP2C19 expression modulates affective functioning and hippocampal subiculum volume-a large single-center community-dwelling cohort study

Given controversial findings of reduced depressive symptom severity and increased hippocampus volume in CYP2C19 poor metabolizers, we sought to provide empirical evidence from a large-scale single-center longitudinal cohort in the community-dwelling adult population-Colaus|PsyCoLaus in Lausanne, Switzerland (n = 4152). We looked for CYP2C19 genotype-related behavioral and brain anatomy patterns using a comprehensive set of psychometry, water diffusion- and relaxometry-based magnetic resonance imaging (MRI) data (BrainLaus, n = 1187). Our statistical models tested for differential associations between poor metabolizer and other metabolizer status with imaging-derived indices of brain volume and tissue properties that explain individuals' current and lifetime mood characteristics. The observed association between CYP2C19 genotype and lifetime affective status showing higher functioning scores in poor metabolizers, was mainly driven by female participants (ß = 3.9, p = 0.010). There was no difference in total hippocampus volume between poor metabolizer and other metabolizer, though there was higher subiculum volume in the right hippocampus of poor metabolizers (ß = 0.03, p_FDRcorrected = 0.036). Our study supports the notion of association between mood phenotype and CYP2C19 genotype, however, finds no evidence for concomitant hippocampus volume differences, with the exception of the right subiculum.

In vivo Estimation of Axonal Morphology From Magnetic Resonance Imaging and Electroencephalography Data

Purpose

We present a novel approach that allows the estimation of morphological features of axonal fibers from data acquired in vivo in humans. This approach allows the assessment of white matter microscopic properties non-invasively with improved specificity.

Theory

The proposed approach is based on a biophysical model of Magnetic Resonance Imaging (MRI) data and of axonal conduction velocity estimates obtained with Electroencephalography (EEG). In a white matter tract of interest, these data depend on (1) the distribution of axonal radius [P(r)] and (2) the g-ratio of the individual axons that compose this tract [g(r)]. P(r) is assumed to follow a Gamma distribution with mode and scale parameters, M and θ, and g(r) is described by a power law with parameters α and β.

Methods

MRI and EEG data were recorded from 14 healthy volunteers. MRI data were collected with a 3T scanner. MRI-measured g-ratio maps were computed and sampled along the visual transcallosal tract. EEG data were recorded using a 128-lead system with a visual Poffenberg paradigm. The interhemispheric transfer time and axonal conduction velocity were computed from the EEG current density at the group level. Using the MRI and EEG measures and the proposed model, we estimated morphological properties of axons in the visual transcallosal tract.

Results

The estimated interhemispheric transfer time was 11.72 ± 2.87 ms, leading to an average conduction velocity across subjects of 13.22 ± 1.18 m/s. Out of the 4 free parameters of the proposed model, we estimated θ – the width of the right tail of the axonal radius distribution – and β – the scaling factor of the axonal g-ratio, a measure of fiber myelination. Across subjects, the parameter θ was 0.40 ± 0.07 μm and the parameter β was 0.67 ± 0.02 μm^−α.

Conclusion

The estimates of axonal radius and myelination are consistent with histological findings, illustrating the feasibility of this approach. The proposed method allows the measurement of the distribution of axonal radius and myelination within a white matter tract, opening new avenues for the combined study of brain structure and function, and for in vivo histological studies of the human brain.

Epidermal Growth Factor Pathway in the Age-Related Decline of Oligodendrocyte Regeneration

Oligodendrocytes (OLs) are specialized glial cells that myelinate CNS axons. OLs are generated throughout life from oligodendrocyte progenitor cells (OPCs) via a series of tightly controlled differentiation steps. Life-long myelination is essential for learning and to replace myelin lost in age-related pathologies such as Alzheimer's disease (AD) as well as white matter pathologies such as multiple sclerosis (MS). Notably, there is considerable myelin loss in the aging brain, which is accelerated in AD and underpins the failure of remyelination in secondary progressive MS. An important factor in age-related myelin loss is a marked decrease in the regenerative capacity of OPCs. In this review, we will contextualize recent advances in the key role of Epidermal Growth Factor (EGF) signaling in regulating multiple biological pathways in oligodendroglia that are dysregulated in aging.

Insights into human cerebral white matter maturation and degeneration across the adult lifespan

White matter (WM) microstructural properties change across the adult lifespan and with neuronal diseases. Understanding microstructural changes due to aging is paramount to distinguish them from neuropathological changes. Conducted on a large cohort of 147 cognitively unimpaired subjects, spanning a wide age range of 21 to 94 years, our study evaluated sex- and age-related differences in WM microstructure. Specifically, we used diffusion tensor imaging (DTI) magnetic resonance imaging (MRI) indices, sensitive measures of myelin and axonal density in WM, and myelin water fraction (MWF), a measure of the fraction of the signal of water trapped within the myelin sheets, to probe these differences. Furthermore, we examined regional correlations between MWF and DTI indices to evaluate whether the DTI metrics provide information complementary to MWF. While sexual dimorphism was, overall, nonsignificant, we observed region-dependent differences in MWF, that is, myelin content, and axonal density with age and found that both exhibit nonlinear, but distinct, associations with age. Furthermore, DTI indices were moderately correlated with MWF, indicating their good sensitivity to myelin content as well as to other constituents of WM tissue such as axonal density. The microstructural differences captured by our MRI metrics, along with their weak to moderate associations with MWF, strongly indicate the potential value of combining these outcome measures in a multiparametric approach. Furthermore, our results support the last-in-first-out and the gain-predicts-loss hypotheses of WM maturation and degeneration. Indeed, our results indicate that the posterior WM regions are spared from neurodegeneration as compared to anterior regions, while WM myelination follows a temporally symmetric time course across the adult life span.

Brain-age estimation accuracy is significantly increased using multishell free-water reconstruction

Although free-water diffusion reconstruction for diffusion-weighted imaging (DWI) data can be applied to both single-shell and multishell data, recent finding in synthetic data suggests that the free-water indices from single-shell acquisition should be interpreted with care, as they are heavily influenced by initialization parameters and cannot discriminate between free-water and mean diffusivity modifications. However, whether using a longer multishell acquisition protocol significantly improve reconstruction for real human MRI data is still an open question. In this study, we compare canonical diffusion tensor imaging (DTI), single-shell and multishell free-water imaging (FW) indices derived from a short, clinical compatible diffusion protocol (b = 500 s/mm² , b = 1,000 s/mm² , 32 directions each) on their power to predict brain age. Age was chosen as it is well-known to be related to widespread modification of the white matter and because brain-age estimation has recently been found to be relevant to several neurodegenerative diseases. We used a previously developed and validated data-driven whole-brain machine learning pipeline to directly compare the precision of brain-age estimates in a sample of 89 healthy males between 20 and 85 years old. We found that multishell FW outperform DTI indices in estimating brain age and that multishell FW, even when using low (500 ms² ) b-values secondary shell, outperform single-shell FW. Single-shell FW led to lower brain-age estimation accuracy even of canonical DTI indices, suggesting that single-shell FW indices should be used with caution. For all considered reconstruction algorithms, the most discriminant indices were those measuring free diffusion of water in the white matter.

Restoring statistical validity in group analyses of motion-corrupted MRI data

Motion during the acquisition of magnetic resonance imaging (MRI) data degrades image quality, hindering our capacity to characterise disease in patient populations. Quality control procedures allow the exclusion of the most affected images from analysis. However, the criterion for exclusion is difficult to determine objectively and exclusion can lead to a suboptimal compromise between image quality and sample size. We provide an alternative, data‐driven solution that assigns weights to each image, computed from an index of image quality using restricted maximum likelihood. We illustrate this method through the analysis of quantitative MRI data. The proposed method restores the validity of statistical tests, and performs near optimally in all brain regions, despite local effects of head motion. This method is amenable to the analysis of a broad type of MRI data and can accommodate any measure of image quality.

Apolipoprotein ε4 modifies obesity-related atrophy in the hippocampal formation of cognitively healthy adults

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Age-related inverted U-shaped curve of hippocampal myelin/neurite packing.

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Reduced hippocampal myelin/neurite packing and size/complexity in obesity.

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APOE modifies the effects of obesity on hippocampal size/complexity.

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Age-related slowing of spatial navigation but no risk effects on cognition.

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CA/DG predict episodic memory and subiculum predicts spatial navigation performance.

Characterizing age- and risk-related hippocampal vulnerabilities may inform about the neural underpinnings of cognitive decline. We studied the impact of three risk-factors, Apolipoprotein (APOE)-ε4, a family history of dementia, and central obesity, on the CA1, CA2/3, dentate gyrus and subiculum of 158 cognitively healthy adults (38-71 years). Subfields were labelled with the Automatic Segmentation of Hippocampal Subfields and FreeSurfer (version 6) protocols. Volumetric and microstructural measurements from quantitative magnetization transfer and Neurite Orientation Density and Dispersion Imaging were extracted for each subfield and reduced to three principal components capturing apparent myelin/neurite packing, size/complexity, and metabolism. Aging was associated with an inverse U-shaped curve on myelin/neurite packing and affected all subfields. Obesity led to reductions in myelin/neurite packing and size/complexity regardless of APOE and family history of dementia status. However, amongst individuals with a healthy Waist-Hip-Ratio, APOE ε4 carriers showed lower size/complexity than non-carriers. Segmentation protocol type did not affect this risk pattern. These findings reveal interactive effects between APOE and central obesity on the hippocampal formation of cognitively healthy adults.

White matter association tracts underlying language and theory of mind: An investigation of 809 brains from the Human Connectome Project

Language and theory of mind (ToM) are the cognitive capacities that allow for the successful interpretation and expression of meaning. While functional MRI investigations are able to consistently localize language and ToM to specific cortical regions, diffusion MRI investigations point to an inconsistent and sometimes overlapping set of white matter tracts associated with these two cognitive domains. To further examine the white matter tracts that may underlie these domains, we use a two-tensor tractography method to investigate the white matter microstructure of 809 participants from the Human Connectome Project. 20 association white matter tracts (10 in each hemisphere) are uniquely identified by leveraging a neuroanatomist-curated automated white matter tract atlas. The fractional anisotropy (FA), mean diffusivity (MD), and number of streamlines (NoS) are measured for each white matter tract. Performance on neuropsychological assessments of semantic memory (NIH Toolbox Picture Vocabulary Test, TPVT) and emotion perception (Penn Emotion Recognition Test, PERT) are used to measure critical subcomponents of the language and ToM networks, respectively. Regression models are constructed to examine how structural measurements of left and right white matter tracts influence performance across these two assessments. We find that semantic memory performance is influenced by the number of streamlines of the left superior longitudinal fasciculus III (SLF-III), and emotion perception performance is influenced by the number of streamlines of the right SLF-III. Additionally, we find that performance on both semantic memory & emotion perception is influenced by the FA of the left arcuate fasciculus (AF). The results point to multiple, overlapping white matter tracts that underlie the cognitive domains of language and ToM. Results are discussed in terms of hemispheric dominance and concordance with prior investigations.

Along-tract analysis of the white matter is more informative about brain ageing, compared to whole-tract analysis

Diffusion Tensor Imaging (DTI) enabled the investigation of brain White Matter (WM), both qualitatively to study the macrostructure, and quantitatively to study the microstructure. The quantitative analyses are mostly performed at the whole-tract level, i.e., providing one measure of interest per tract; however, along-tract approaches may provide finer details of the quality of the WM tracts. In this study, using the DWI data collected from 40 young and 40 old individuals, we compared the DTI measures of FA, MD, AD, and RD, estimated by both whole-tract and along-tract approaches in 18 WM bundles, between the two groups. The results of the whole-tract quantitative analysis showed a statistically significant (p-FWER < 0.05) difference between the old and young groups in 6 tracts for FA, 8 tracts for MD, 1 tract for AD, and 7 tracts for RD. On the contrary, the along-tract approach showed differences between the two groups in 10 tracts for FA, 14 tracts for MD, 8 tracts for AD, and 11 tracts for RD. All the differences between the along-tract measures of the two groups had a large effect size (Cohen'd > 0.80). This study showed that the along-tract approach for the analysis of brain WM reveals changes in some WM tracts which had not shown any changes in the whole-tract approach, and therefore this finding emphasizes the utilization of the along-tract approach along with the whole-tract method for a more accurate study of the brain WM.

Investigating impact of cardiorespiratory fitness in reducing brain tissue loss caused by ageing

Mitigating the loss of brain tissue due to age is a major problem for an ageing population. Improving cardiorespiratory fitness has been suggested as a possible strategy, but the influenceon brain morphology has not been fully characterized. To investigate the dependent shifts in brain tissue distribution as a function of cardiorespiratory fitness, we used a 3D transport-based morphometry approach. In this study of 172 inactive older adults aged 58-81 (66.5 ± 5.7) years, cardiorespiratory fitness was determined by VO 2 peak (ml/kg/min) during graded exercise and brain morphology was assessed through structural magnetic resonance imaging. After correcting for covariates including age (in the fitness model), gender and level of education, we compared dependent tissue shifts with age to those due to V O 2   peak . We found a significant association between cardiorespiratory fitness and brain tissue distribution (white matter, r = 0.30, P = 0.003; grey matter, r = 0.40, P < 0.001) facilitated by direct visualization of the brain tissue shifts due to cardiorespiratory fitness through inverse transformation-a key capability of 3D transport-based morphometry. A strong statistical correlation was found between brain tissue changes related to ageing and those associated with lower cardiorespiratory fitness (white matter, r = 0.62, P < 0.001; grey matter, r = 0.74, P < 0.001). In both cases, frontotemporal regions shifted the most while basal ganglia shifted the least. Our results highlight the importance of cardiorespiratory fitness in maintaining brain health later in life. Furthermore, this work demonstrates 3D transport-based morphometry as a novel neuroinformatic technology that may aid assessment of therapeutic approaches for brain ageing and neurodegenerative diseases.