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As Alzheimer’s disease (AD) pathology accumulates, resting-state functional connectivity (rs-fc) within and between brain networks decreases, and fluctuations in cognitive performance known as intraindividual variability (IIV) increase. Here, we assessed the relationship between IIV and anticorrelations in rs-fc between the default mode network (DMN)-dorsal attention network (DAN) in cognitively normal older adults and symptomatic AD participants. We also evaluated the relationship between cerebrospinal fluid (CSF) biomarkers of AD (amyloid-beta [Aβ42] and tau) and IIV-anticorrelation in rs-fc. We observed that cognitive IIV and anticorrelations between DMN × DAN were higher in individuals with AD compared with cognitively normal participants. As DMN × DAN relationship became more positive, cognitive IIV increased, indicating that stronger anticorrelations between networks support more consistent cognitive performance. Moderation analyses indicated that continuous CSF Aβ42, but not CSF total tau, moderated the relationship between cognitive IIV and DMN × DAN, collectively demonstrating that greater amyloid burden and alterations in functional network dynamics are associated with cognitive changes seen in AD. These findings are valuable, as they suggest that amyloid affects cognitive functioning during the early stages of AD.

Visual short-term memory (vSTM) is a cognitive resource that declines with age. This study investigated whether electroencephalography (EEG) correlates of vSTM vary with cognitive development over individuals' lifespan. We measured vSTM performance and EEG in a lateralized whole-report task in a healthy birth cohort, whose cognitive function (intelligence quotient) was assessed in youth and late-middle age. Higher vSTM capacity (K; measured by Bundesen's theory of visual attention) was associated with higher amplitudes of the contralateral delay activity (CDA) and the central positivity (CP). In addition, rightward hemifield asymmetry of vSTM (Kλ) was associated with lower CDA amplitudes. Furthermore, more severe cognitive decline from young adulthood to late-middle age predicted higher CDA amplitudes, and the relationship between K and the CDA was less reliable in individuals who show higher levels of cognitive decline compared to individuals with preserved abilities. By contrast, there was no significant effect of lifespan cognitive changes on the CP or the relationship between behavioral measures of vSTM and the CP. Neither the CDA, nor the CP, nor the relationships between K or Kλ and the event-related potentials were predicted by individuals' current cognitive status. Together, our findings indicate complex age-related changes in processes underlying behavioral and EEG measures of vSTM and suggest that the K-CDA relationship might be a marker of cognitive lifespan trajectories.

Computational anatomy with magnetic resonance imaging (MRI) is well established as a noninvasive biomarker of Alzheimer’s disease (AD); however, there is less certainty about its dependency on the staging of AD. We use classical group analyses and automated machine learning classification of standard structural MRI scans to investigate AD diagnostic accuracy from the preclinical phase to clinical dementia. Longitudinal data from the Alzheimer’s Disease Neuroimaging Initiative were stratified into 4 groups according to the clinical statusd(1) AD patients; (2) mild cognitive impairment (MCI) converters; (3) MCI nonconverters; and (4) healthy controlsdand submitted to a support vector machine. The obtained classifier was significantly above the chance level (62%) for detecting AD already 4 years before conversion from MCI. Voxel-based univariate tests confirmed the plausibility of our findings detecting a distributed network of hippocampal-temporoparietal atrophy in AD patients. We also identified a subgroup of control subjects with brain structure and cognitive changes highly similar to those observed in AD. Our results indicate that computational anatomy can detect AD substantially earlier than suggested by current models. The demonstrated differential spatial pattern of atrophy between correctly and incorrectly classified AD patients challenges the assumption of a uniform pathophysiological process underlying clinically identified AD.

Objective To examine the association of salivary cortisol with cognitive changes in a 3 year longitudinal study. Previous studies have suggested that elevated glucocorticoid concentrations alter hippocampal neuronal morphology, inhibit neurogenesis, and impair cognition. Methods Salivary cortisol samples were collected at home by 79 cognitively intact older persons (mean age 78 ± 7 years) at 08:00, 15:00 and 23:00 h, and collections were repeated annually for 3 years. Cognitive function was also assessed annually. Results The mean cortisol level of samples taken at three times of day and the cortisol concentration at 23:00 h were significantly associated with poorer performance on tasks of declarative memory and executive function. Of 46 subjects who completed the entire 3 year study, higher initial cortisol concentration at 23:00 h predicted a decline in performance of delayed paragraph recall. Conclusion These results partially confirm previous findings that high cortisol is associated with impaired declarative memory function in non-demented older persons. In addition, our data show that high salivary cortisol concentrations predict a decline in memory function over the next 3 years.

As part of an effort to characterize age-related cognitive changes in executive system function in a nonhuman primate model of human aging, the performance of seven rhesus monkeys, 20 to 28 years of age, was compared to that of five young adult monkeys, 6 to 11 years of age, on spatial and object reversal tasks. No differences in performance were found between the two groups in the initial learning of either task. On spatial reversals, aged monkeys were impaired relative to young adults, but there was no difference in overall performance between the groups on object reversals. Central to this article, a perseverative tendency was noted in the aged group on both spatial and object reversal tasks. Changes in executive system dysfunction may represent an important aspect of age-related cognitive decline.

Parametric manipulation of experimental variables is important for both practical and theoretical reasons. Practically, age-related impairments in memory may be detected only at certain levels of difficulty. If the task is too simple, age-related cognitive impairments may not be sufficient to alter performance. If the task is too difficult, age-related cognitive impairments may not add significantly to the poor performance of younger controls. Thus, some intermediate level of difficulty is necessary to produce behavioral evidence on underlying age-related cognitive changes. Theoretically, parametric manipulations are important to identify the psychological processes responsible for the behavioral alterations. For example, consider the common finding of an age-related impairment in a delayed conditional discrimination task. If that impairment is produced by a primary deficit in recent memory, then the magnitude of the age-related impairment should increase with the length as the delay interval is increased, producing a statistical interaction between the age delay interval. Both the practical and theoretical considerations are illustrated with specific experiments, and have implications for the types of experimental design that can be most effective in demonstrating and explaining age-related changes in learning and memory.

Useful models of age-related human and animal memory changes should simulate specific features of cognitive impairment associated with aging. It is necessary but not sufficient to demonstrate that manipulations such as those produced by lesions and drugs cause impairments in some cognitive function such as memory. A useful model should be able to reproduce a pattern of cognitive changes in which islands of spared versus impaired functioning resemble those associated with aging and differ from those produced by other conditions. This requires the use of research strategies utilizing multivariate treatment and dependent measure designs. The papers in this section illustrate the value of such a research approach.