Several theories of cognitive compensation have been suggested to explain sustained cognitive abilities in healthy brain aging and early neurodegenerative processes. The growing number of studies investigating various aspects of task-based compensation in these conditions is contrasted by the shortage of data about resting-state compensatory mechanisms. Using our proposed criterion-based framework for compensation, we investigated 45 participants in three groups: (i) patients with mild cognitive impairment (MCI) and positive biomarkers indicative of Alzheimer's disease (AD); (ii) cognitively normal young adults; (iii) cognitively normal older adults. To increase reliability, three sessions of resting-state functional magnetic resonance imaging for each participant were performed on different days (135 scans in total). To elucidate the dimensions and dynamics of resting-state compensatory mechanisms, we used graph theory analysis along with volumetric analysis. Graph theory analysis was applied based on the Brainnetome atlas, which provides a connectivity-based parcellation framework. Comprehensive neuropsychological examinations including the Rey Auditory Verbal Learning Test (RAVLT) and the Trail Making Test (TMT) were performed, to relate graph measures of compensatory nodes to cognition. To avoid false-positive findings, results were corrected for multiple comparisons. First, we observed an increase of degree centrality in cognition related brain regions of the middle frontal gyrus, precentral gyrus and superior parietal lobe despite local atrophy in MCI and healthy aging, indicating a resting-state connectivity increase with positive biomarkers. When relating the degree centrality measures to cognitive performance, we observed that greater connectivity led to better RAVLT and TMT scores in MCI and, hence, might constitute a compensatory mechanism. The detection and improved understanding of the compensatory dynamics in healthy aging and prodromal AD is mandatory for implementing and tailoring preventive interventions aiming at preserved overall cognitive functioning and delayed clinical onset of dementia.

Aging is associated with memory decline and progressive disabilities in the activities of daily living. These deficits have a significant impact on the quality of life of the aging population and lead to a tremendous burden on societies and health care systems. Understanding the mechanisms underlying aging-related memory decline is likely to inform the development of compensatory strategies promoting independence in old age. Research on aging-related memory decline has mainly focused on encoding and retrieval. However, some findings suggest that memory deficits may at least partly be due to impaired consolidation. To date, it remains elusive whether aging-related memory decline results from defective consolidation. This study examined age effects on consolidation-related neural mechanisms and their susceptibility to interference using functional magnetic resonance imaging data from 13 younger (20–30 years, 8 female) and 16 older (49–75 years, 5 female) healthy participants. fMRI was performed before and during a memory paradigm comprised of encoding, consolidation, and retrieval phases. Consolidation was variously challenged: (1) control (no manipulation), (2) interference (repeated stimulus presentation with interfering information), and (3) reminder condition (repeated presentation without interfering information). We analyzed the fractional amplitude of low-frequency fluctuations (fALFF) to compare brain activity changes from pre- to post-encoding rest. In the control condition, fALFF was decreased in the left supramarginal gyrus, right middle temporal gyrus, and left precuneus but increased in parts of the occipital and inferior temporal cortex. Connectivity analyses between fALFF-derived seeds and network ROIs revealed an aging-related decrease in the efficiency of functional connectivity (FC) within the ventral stream network and between salience, default mode, and central executive networks during consolidation. Moreover, our results indicate increased interference susceptibility in older individuals with dynamics between salience and default mode networks as a neurophysiological correlate. Conclusively, aging-related memory decline is partly caused by inefficient consolidation. Memory consolidation requires a complex interplay between large-scale brain networks, which qualitatively decreases with age.