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.

Neuropsychological deficits among patients with late-onset minor and major depression.

Cognitive ability of minor depressed patients (N=28), major depressed patients (N=26) and healthy elderly (N=38) was examined cross-sectionally to determine if cognitive abilities of patients with late-onset depression decrease with increasing severity of disease and if cognitive scores for minor depressed patients fall between those of healthy elderly and major depressed patients. A pooled within-group principal component analysis of cognitive test scores identified five components, three of which showed significant group differences. Verbal Recall and Maintenance of Set separated controls from major depressed patients and minor from major depressed patients. Executive Functioning separated controls from minor depressed patients, and Working Memory was borderline for separating controls from major depressed patients. The component representing Nonverbal Recognition was not statistically significant. Partial correlations controlling for age and education indicate that cognitive performance does decrease as severity of depression increases, and the magnitude of the change varies from a trend to a significant deficit depending on the cognitive domain. This decline in cognitive performance parallels a similar trend observed in neuroanatomical studies in which the volume of the frontal and temporal lobes decrease with increasing severity of depression.