Investigating White Matter Lesion Load, Intrinsic Functional Connectivity, and Cognitive Abilities in Older Adults

Changes to the while matter of the brain disrupt neural communication between spatially distributed brain regions and are associated with cognitive changes in later life. While approximately 95% of older adults experience these brain changes, not everyone who has significant white matter damage displays cognitive impairment. Few studies have investigated the association between white matter changes and cognition in the context of functional brain network integrity. This study used a data-driven, multivariate analytical model to investigate intrinsic functional connectivity patterns associated with individual variability in white matter lesion load as related to fluid and crystallized intelligence in a sample of healthy older adults (n = 84). Several primary findings were noted. First, a reliable pattern emerged associating whole-brain resting-state functional connectivity with individual variability in measures of white matter lesion load, as indexed by total white matter lesion volume and number of lesions. Secondly, white matter lesion load was associated with increased network disintegration and dedifferentiation. Specifically, lower white matter lesion load was associated with greater within- versus between-network connectivity. Higher white matter lesion load was associated with greater between-network connectivity compared to within. These associations between intrinsic functional connectivity and white matter lesion load were not reliably associated with crystallized and fluid intelligence performance. These results suggest that changes to the white matter of the brain in typically aging older adults are characterized by increased functional brain network dedifferentiation. The findings highlight the role of white matter lesion load in altering the functional network architecture of the brain

White Matter Abnormalities in Patients with Treatment-Resistant Genetic Generalized Epilepsies.

BACKGROUND Genetic generalized epilepsies (GGEs) are associated with microstructural brain abnormalities that can be evaluated with diffusion tensor imaging (DTI). Available studies on GGEs have conflicting results. Our primary goal was to compare the white matter structure in a cohort of patients with video/EEG-confirmed GGEs to healthy controls (HCs). Our secondary goal was to assess the potential effect of age at GGE onset on the white matter structure. MATERIAL AND METHODS A convenience sample of 23 patients with well-characterized treatment-resistant GGEs (13 female) was compared to 23 HCs. All participants received MRI at 3T. DTI indices, including fractional anisotropy (FA) and mean diffusivity (MD), were compared between groups using Tract-Based Spatial Statistics (TBSS). RESULTS After controlling for differences between groups, abnormalities in DTI parameters were observed in patients with GGEs, including decreases in functional anisotropy (FA) in the hemispheric (left>right) and brain stem white matter. The examination of the effect of age at GGE onset on the white matter integrity revealed a significant negative correlation in the left parietal white matter region FA (R=-0.504; p=0.017); similar trends were observed in the white matter underlying left motor cortex (R=-0.357; p=0.103) and left posterior limb of the internal capsule (R=-0.319; p=0.148). CONCLUSIONS Our study confirms the presence of widespread white matter abnormalities in patients with GGEs and provides evidence that the age at GGE onset may have an important effect on white matter integrity

Divergent longitudinal propagation of white matter degradation in logopenic and semantic variants of primary progressive aphasia

Background: Clinico-pathological distinction of primary progressive aphasia (PPA) can be challenging at clinic presentation. In particular, cross-sectional neuroimaging signatures across the logopenic (lvPPA) and semantic (svPPA) variants are difficult to establish, with longitudinal profiles showing greater divergence. Objective: Assess longitudinal propagation of white matter degradation in lvPPA and svPPA to determine disease progression over time, and whether this reflects distinct underlying pathology. Method: A cohort of 27 patients with dementia (12 lvPPA; 15 svPPA) and 12 healthy controls were assessed at baseline and 1-year follow-up on the Addenbrooke’s Cognitive Examination-Revised and Sydney Language Battery. Diffusion weighted images were collected at both time-points and analyzed for longitudinal white matter change using DTI-TK and TBSS. Results: LvPPA patients showed a significant decline in naming and repetition, over 1 year, while svPPA patients declined in naming and comprehension. Longitudinal imaging revealed widespread bilateral degradation of white matter tracts in lvPPA over a 1-year period with early involvement of the left posterior inferior longitudinal fasciculus (ILF). SvPPA demonstrated focal left lateralized white matter degradation involving the uncinate fasciculus (UF) and anterior ILF, propagating to the right UF with disease progression. Conclusions: LvPPA and svPPA cohorts showed distinct longitudinal cognitive and white matter profiles. We propose differences in multi-centric and focal white matter dysfunction in lvPPA and svPPA, respectively, reflect underlying pathological differences. The clinical relevance of white matter degradation and mechanisms underlying disease propagation are discussed

Disconnected aging: cerebral white matter integrity and age-related differences in cognition.

Cognition arises as a result of coordinated processing among distributed brain regions and disruptions to communication within these neural networks can result in cognitive dysfunction. Cortical disconnection may thus contribute to the declines in some aspects of cognitive functioning observed in healthy aging. Diffusion tensor imaging (DTI) is ideally suited for the study of cortical disconnection as it provides indices of structural integrity within interconnected neural networks. The current review summarizes results of previous DTI aging research with the aim of identifying consistent patterns of age-related differences in white matter integrity, and of relationships between measures of white matter integrity and behavioral performance as a function of adult age. We outline a number of future directions that will broaden our current understanding of these brain-behavior relationships in aging. Specifically, future research should aim to (1) investigate multiple models of age-brain-behavior relationships; (2) determine the tract-specificity versus global effect of aging on white matter integrity; (3) assess the relative contribution of normal variation in white matter integrity versus white matter lesions to age-related differences in cognition; (4) improve the definition of specific aspects of cognitive functioning related to age-related differences in white matter integrity using information processing tasks; and (5) combine multiple imaging modalities (e.g., resting-state and task-related functional magnetic resonance imaging; fMRI) with DTI to clarify the role of cerebral white matter integrity in cognitive aging

Probing white-matter microstructure with higher-order diffusion tensors and susceptibility tensor MRI.

Diffusion MRI has become an invaluable tool for studying white matter microstructure and brain connectivity. The emergence of quantitative susceptibility mapping and susceptibility tensor imaging (STI) has provided another unique tool for assessing the structure of white matter. In the highly ordered white matter structure, diffusion MRI measures hindered water mobility induced by various tissue and cell membranes, while susceptibility sensitizes to the molecular composition and axonal arrangement. Integrating these two methods may produce new insights into the complex physiology of white matter. In this study, we investigated the relationship between diffusion and magnetic susceptibility in the white matter. Experiments were conducted on phantoms and human brains in vivo. Diffusion properties were quantified with the diffusion tensor model and also with the higher order tensor model based on the cumulant expansion. Frequency shift and susceptibility tensor were measured with quantitative susceptibility mapping and susceptibility tensor imaging. These diffusion and susceptibility quantities were compared and correlated in regions of single fiber bundles and regions of multiple fiber orientations. Relationships were established with similarities and differences identified. It is believed that diffusion MRI and susceptibility MRI provide complementary information of the microstructure of white matter. Together, they allow a more complete assessment of healthy and diseased brains