To examine the relationship between white matter hyperintensity (WMH) volume on magnetic resonance imagesandcognitivetestsinalarge,population-basedsample. Methods: Quantitative magnetic resonance imaging and neuropsychological evaluations were performed in 1820 dementia-and stroke-free participants from the Framingham Offspring Cohort. The WMH volume relative to total cranial volume was computed; WMH volumes more than 1 SD above the age-predicted mean were defined as large. Adjusting for age, sex, education, height, and Framingham Stroke Risk Profile, we examined the relationship between WMH and 3 cognitive factors derived from a neuropsychological test battery (verbal memory, visuospatial memory and organization, and visual scanning and motor speed) and 3 individual measures of new learning, abstract reasoning, and naming.

Behavior arises from the coordinated activity of numerous anatomically and functionally distinct brain regions. Modern experimental tools allow unprecedented access to large neural populations spanning many interacting regions brain-wide. Yet, understanding such large-scale datasets necessitates both scalable computational models to extract meaningful features of interregion communication and principled theories to interpret those features. Here, we introduce Current-Based Decomposition (CURBD), an approach for inferring brain-wide interactions using data-constrained recurrent neural network models that directly reproduce experimentally-obtained neural data. CURBD leverages the functional interactions inferred by such models to reveal directional currents between multiple brain regions. We first show that CURBD accurately isolates inter-region currents in simulated networks with known dynamics. We then apply CURBD to multi-region neural recordings obtained from mice during running, macaques during Pavlovian conditioning, and humans during memory retrieval to demonstrate the widespread applicability of CURBD to untangle brain-wide interactions underlying behavior from a variety of neural datasets.

Aging decreases the density of spines and the proportion of thin spines in the non-human primate (NHP) dorsolateral prefrontal cortex (dlPFC). In this study, we used confocal imaging of dye-loaded neurons to expand upon previous results regarding the effects of aging on spine density and morphology in the NHP dlPFC and compared these results to the effects of aging on pyramidal neurons in primary visual cortex (V1). We confirmed that spine density, and particularly the density of thin spines, decreased with age in the dlPFC of rhesus monkeys. Furthermore, the average head diameter of non-stubby spines in the dlPFC was a better predictor than chronological age of the number of trials required to reach criterion on both the delayed response test of visuospatial working memory and the delayed nonmatching-to-sample test of recognition memory. By contrast, total spine density was lower on neurons in V1 than in dlPFC, and neither total spine density, thin spine density, nor spine size in V1 was affected by aging. Our results highlight the importance and selective vulnerability of dlPFC thin spines for optimal prefrontal-mediated cognitive function. Understanding the nature of the selective vulnerability of dlPFC thin spines as compared to the resilience of thin spines in V1 may be a promising area of research in the quest to prevent or ameliorate age-related cognitive decline.

Aged ovariectomized female monkeys, a model for menopause in humans, show declines in spine density in the dlPFC and diminished performance in cognitive tasks requiring this brain region. Previous studies in our laboratory have shown that long-term cyclic treatment with 17β-estradiol (E) produces an increase in spine density and in the proportion of thinner spines in layer III pyramidal neurons in the dorsolateral prefrontal cortex (dlPFC) of both young and aged ovariectomized rhesus monkeys. Here we used 3D reconstruction of Lucifer yellow-loaded neurons to investigate whether clinically relevant schedules of hormone therapy would produce similar changes in prefrontal cortical neuronal morphology as long-term cyclic E treatment in young female monkeys. We found that continuously delivered E, with or without a cyclic progesterone treatment, did not alter spine density or morphology in the dlPFC of young adult OVX rhesus monkeys. We also found that the increased density of thinner spines evident in the dlPFC 24 hours after E administration in the context of long-term cyclic E therapy is no longer detectable 20 days after E treatment. When compared with the results of our previously published investigations, our results suggest that cyclic fluctuations in serum E levels may cause corresponding fluctuations in the density of thin spines in the dlPFC. By contrast, continuous administration of E does not support sustained increases in thin spine density. Physiological fluctuations in E concentration may be necessary to maintain the morphological sensitivity of the dlPFC to E.