Opposing effects of aging on large-scale brain systems for memory encoding and cognitive control.
ABSTRACT Episodic memory declines with advancing age. Neuroimaging studies have associated such decline to age-related changes in general cognitive-control networks as well as to changes in process-specific encoding or retrieval networks. To assess the specific influence of aging on encoding and retrieval processes and associated brain systems, it is vital to dissociate encoding and retrieval from each other and from shared cognitive-control processes. We used multivariate partial-least-squares to analyze functional magnetic resonance imaging data from a large population-based sample (n = 292, 25-80 years). The participants performed a face-name paired-associates task and an active baseline task. The analysis revealed two significant network patterns. The first reflected a process-general encoding-retrieval network that included frontoparietal cortices and posterior hippocampus. The second pattern dissociated encoding and retrieval networks. The anterior hippocampus was differentially engaged during encoding. Brain scores, representing whole-brain integrated measures of how strongly an individual recruited a brain network, were correlated with cognitive performance and chronological age. The scores from the general cognitive-control network correlated negatively with episodic memory performance and positively with age. The encoding brain scores, which strongly reflected hippocampal functioning, correlated positively with episodic memory performance and negatively with age. Univariate analyses confirmed that bilateral hippocampus showed the most pronounced activity reduction in older age, and brain structure analyses found that the activity reduction partly related to hippocampus atrophy. Collectively, these findings suggest that age-related structural brain changes underlie age-related reductions in the efficient recruitment of a process-specific encoding network, which cascades into upregulated recruitment of a general cognitive-control network.
- SourceAvailable from: Joshua H Balsters[show abstract] [hide abstract]
ABSTRACT: Electrophysiology studies routinely investigate the relationship between neural oscillations and task performance. However, the sluggish nature of the BOLD response means that few researchers have investigated the spectral properties of the BOLD signal in a similar manner. For the first time we have applied group ICA to fMRI data collected during a standard working memory task (delayed match-to-sample) and using a multivariate analysis, we investigate the relationship between working memory performance (accuracy and reaction time) and BOLD spectral power within functional networks. Our results indicate that BOLD spectral power within specific networks (visual, temporal-parietal, posterior default-mode network, salience network, basal ganglia) correlated with task accuracy. Multivariate analyses show that the relationship between task accuracy and BOLD spectral power is stronger than the relationship between BOLD spectral power and other variables (age, gender, head movement, and neuropsychological measures). A traditional General Linear Model (GLM) analysis found no significant group differences, or regions that covaried in signal intensity with task accuracy, suggesting that BOLD spectral power holds unique information that is lost in a standard GLM approach. We suggest that the combination of ICA and BOLD spectral power is a useful novel index of cognitive performance that may be more sensitive to brain-behavior relationships than traditional approaches.Frontiers in Human Neuroscience 01/2013; 7:207. · 2.91 Impact Factor
- [show abstract] [hide abstract]
ABSTRACT: Resting fluctuations in the blood oxygenation level-dependent signal have attracted considerable interest for their sensitivity to pathological brain processes. However, these analyses are susceptible to confound by nonneural physiological factors such as vasculature, breathing, and head movement which is a concern when investigating elderly or pathological groups. Here, we used simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) (EEG/fMRI) to constrain the analysis of resting state networks (RSNs) and identify aging differences. Four of 26 RSNs showed fMRI and EEG/fMRI group differences; anterior default-mode network, left frontal-parietal network, bilateral middle frontal, and postcentral gyri. Seven RSNs showed only EEG/fMRI differences suggesting the combination of these 2 methods might be more sensitive to age-related neural changes than fMRI alone. Five RSNs showed only fMRI differences and might reflect nonneural group differences. Activity within some EEG/fMRI RSNs was better explained by neuropsychological measures (Mini Mental State Examination and Stroop) than age. These results support previous studies suggesting that age-related changes in specific RSNs are neural in origin, and show that changes in some RSNs relate better to elderly cognition than age.Neurobiology of aging 04/2013; · 5.94 Impact Factor