Search

Objective: To determine whether volumetric measures of the hippocampus, entorhinal cortex, and other cortical measures can differentiate between cognitively normal individuals and subjects with mild cognitive impairment (MCI)., Method: Magnetic resonance imaging (MRI) data from 46 cognitively normal subjects and 50 subjects with MCI as part of the Boston University Alzheimer's Disease Center research registry and the Alzheimer's Disease Neuroimaging Initiative were used in this cross-sectional study. Cortical, subcortical, and hippocampal subfield volumes were generated from each subject's MRI data using FreeSurfer v6.0. Nominal logistic regression models containing these variables were used to identify subjects as control or MCI., Results: A model containing regions of interest (superior temporal cortex, caudal anterior cingulate, pars opercularis, subiculum, precentral cortex, caudal middle frontal cortex, rostral middle frontal cortex, pars orbitalis, middle temporal cortex, insula, banks of the superior temporal sulcus, parasubiculum, paracentral lobule) fit the data best (R2 = .7310, whole model test chi-square = 97.16, p < .0001)., Conclusions: MRI data correctly classified most subjects using measures of selected medial temporal lobe structures in combination with those from other cortical areas, yielding an overall classification accuracy of 93.75%. These findings support the notion that, while volumes of medial temporal lobe regions differ between cognitively normal and MCI subjects, differences that can be used to distinguish between these two populations are present elsewhere in the brain.

Background: Deterministic diffusion tractography obtained from high angular resolution diffusion imaging (HARDI) requires user-defined quantitative anisotropy (QA) thresholds. Most studies employ a common threshold across all subjects even though there is a strong degree of individual variation within groups. We sought to explore whether it would be beneficial to use individual thresholds in order to accommodate individual variance. To do this, we conducted two independent experiments., Method: First, tractography of the arcuate fasciculus and network connectivity measures were examined in a sample of 14 healthy participants. Second, we assessed the effects of QA threshold on group differences in network connectivity measures between healthy young (n=19) and old (n=14) individuals., Results: The results of both experiments were significantly influenced by QA threshold. Common thresholds set too high failed to produce sufficient reconstructions in most subjects, thus decreasing the likelihood of detecting meaningful group differences. On the other hand, common thresholds set too low resulted in spurious reconstructions, providing deleterious results., Comparison With Existing Methods: Subject specific thresholds acquired using our QA threshold selection method (QATS) appeared to provide the most meaningful networks while ensuring that data from all subjects contributed to the analyses., Conclusions: Together, these results support the use of a subject-specific threshold to ensure that data from all subjects are included in the analyses being conducted., (Copyright © 2017 Elsevier B.V. All rights reserved.)

The goal of this study was to examine whether hippocampal volume or resting-state functional connectivity (rsFC) patterns are associated with subjective memory decline (SMD) in cognitively normal aged adults. Magnetic resonance imaging data from 53 participants (mean age: 71.9 years) of the Boston University Alzheimer's Disease Center registry were used in this cross-sectional study. Separate analyses treating SMD as a binary and continuous variable were performed. Subfield volumes were generated using FreeSurfer v6.0, and rsFC strength between the head and body of the hippocampus and the rest of the brain was calculated. Decreased left whole hippocampal volume and weaker rsFC strength between the right body of the hippocampus and the default mode network (DMN) were found in SMD+. Cognitive Change Index score was not correlated with volumetric measures but was inversely correlated with rsFC strength between the right body of the hippocampus and 6 brain networks, including the DMN, task control, and attentional networks. These findings suggest that hippocampal rsFC patterns reflect the current state of SMD in cognitively normal adults and may reflect subtle memory changes that standard neuropsychological tests are unable to capture. [ABSTRACT FROM AUTHOR]

Spatial navigation is a cognitive skill fundamental to successful interaction with our environment, and aging is associated with weaknesses in this skill. Identifying mechanisms underlying individual differences in navigation ability in aged adults is important to understanding these age-related weaknesses. One understudied factor involved in spatial navigation is self-motion perception. Important to self-motion perception is optic flow–the global pattern of visual motion experienced while moving through our environment. A set of optic flow-sensitive (OF-sensitive) cortical regions was defined in a group of young (n = 29) and aged (n = 22) adults. Brain activity was measured in this set of OF-sensitive regions and control regions using functional magnetic resonance imaging while participants performed visual path integration (VPI) and turn counting (TC) tasks. Aged adults had stronger activity in RMT+ during both tasks compared to young adults. Stronger activity in the OF-sensitive regions LMT+ and RpVIP during VPI, not TC, was associated with greater VPI accuracy in aged adults. The activity strength in these two OF-sensitive regions measured during VPI explained 42% of the variance in VPI task performance in aged adults. The results of this study provide novel support for global motion processing as a mechanism underlying visual path integration in normal aging. [ABSTRACT FROM AUTHOR]