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We studied oscillatory mechanisms of memory formation in 48 younger and 51 older adults in an intentional associative memory task with cued recall. While older adults showed lower memory performance than young adults, we found subsequent memory effects (SME) in alpha/beta and theta frequency bands in both age groups. Using logistic mixed effects models, we investigated whether interindividual differences in structural integrity of key memory regions could account for interindividual differences in the strength of the SME. Structural integrity of inferior frontal gyrus (IFG) and hippocampus was reduced in older adults. SME in the alpha/beta band were modulated by the cortical thickness of IFG, in line with its hypothesized role for deep semantic elaboration. Importantly, this structure–function relationship did not differ by age group. However, older adults were more frequently represented among the participants with low cortical thickness and consequently weaker SME in the alpha band. Thus, our results suggest that differences in the structural integrity of the IFG contribute not only to interindividual, but also to age differences in memory formation.

Successful consolidation of associative memories relies on the coordinated interplay of slow oscillations and sleep spindles during non-rapid eye movement (NREM) sleep. This enables the transfer of labile information from the hippocampus to permanent memory stores in the neocortex. During senescence, the decline of the structural and functional integrity of the hippocampus and neocortical regions is paralleled by changes of the physiological events that stabilize and enhance associative memories during NREM sleep. However, the currently available evidence is inconclusive as to whether and under which circumstances memory consolidation is impacted during aging. To approach this question, 30 younger adults (19–28 years) and 36 older adults (63–74 years) completed a memory task based on scene–word associations. By tracing the encoding quality of participants’ individual memory associations, we demonstrate that previous learning determines the extent of age-related impairments in memory consolidation. Specifically, the detrimental effects of aging on memory maintenance were greatest for mnemonic contents of intermediate encoding quality, whereas memory gain of poorly encoded memories did not differ by age. Ambulatory polysomnography (PSG) and structural magnetic resonance imaging (MRI) data were acquired to extract potential predictors of memory consolidation from each participant’s NREM sleep physiology and brain structure. Partial Least Squares Correlation was used to identify profiles of interdependent alterations in sleep physiology and brain structure that are characteristic for increasing age. Across age groups, both the ‘aged’ sleep profile, defined by decreased slow-wave activity (0.5–4.5 ​Hz), and a reduced presence of slow oscillations (0.5–1 ​Hz), slow, and fast spindles (9–12.5 ​Hz; 12.5–16 ​Hz), as well as the ‘aged’ brain structure profile, characterized by gray matter reductions in the medial prefrontal cortex, thalamus, entorhinal cortex, and hippocampus

Age-related memory decline is associated with changes in neural functioning, but little is known about how aging affects the quality of information representation in the brain. Whereas a long-standing hypothesis of the aging literature links cognitive impairments to less distinct neural representations in old age (“neural dedifferentiation”), memory studies have shown that overlapping neural representations of different studied items are beneficial for memory performance. In an electroencephalography (EEG) study, we addressed the question whether distinctiveness or similarity between patterns of neural activity supports memory differentially in younger and older adults. We analyzed between-item neural pattern similarity in 50 younger (19–27 years old) and 63 older (63–75 years old) male and female human adults who repeatedly studied and recalled scene–word associations using a mnemonic imagery strategy. We compared the similarity of spatiotemporal EEG frequency patterns during initial encoding in relation to subsequent recall performance. The within-person association between memory success and pattern similarity differed between age groups: For older adults, better memory performance was linked to higher similarity early in the encoding trials, whereas young adults benefited from lower similarity between earlier and later periods during encoding, which might reflect their better success in forming unique memorable mental images of the joint picture–word pairs. Our results advance the understanding of the representational properties that give rise to subsequent memory, as well as how these properties may change in the course of aging.

Successful consolidation of associative memories relies on the coordinated interplay of slow oscillations and sleep spindles during non-rapid eye movement (NREM) sleep, enabling the transfer of labile information from the hippocampus to permanent memory stores in the neocortex. During senescence, the decline of the structural and functional integrity of the hippocampus and neocortical regions is paralleled by changes of the physiological events that stabilize and enhance associative memories during NREM sleep. However, the currently available evidence is inconclusive if and under which circumstances aging impacts memory consolidation. By tracing the encoding quality of single memories in individual participants, we demonstrate that previous learning determines the extent of age-related impairments in memory consolidation. Specifically, the detrimental effects of aging on memory maintenance were greatest for mnemonic contents of medium encoding quality, whereas memory gain of weakly encoded memories did not differ by age. Using multivariate techniques, we identified profiles of alterations in sleep physiology and brain structure characteristic for increasing age. Importantly, while both ‘aged’ sleep and ‘aged’ brain structure profiles were associated with reduced memory maintenance, inter-individual differences in neither sleep nor structural brain integrity qualified as the driving force behind age differences in sleep-dependent consolidation in the present study.

Age-related memory decline is associated with changes in neural functioning but little is known about how aging affects the quality of information representation in the brain. Whereas a long-standing hypothesis of the aging literature links cognitive impairments to less distinct neural representations in old age, memory studies have shown that high similarity between activity patterns benefits memory performance for the respective stimuli. Here, we addressed this apparent conflict by investigating between-item representational similarity in 50 younger (19–27 years old) and 63 older (63–75 years old) human adults (male and female) who studied scene-word associations using a mnemonic imagery strategy while electroencephalography was recorded. We compared the similarity of spatiotemporal frequency patterns elicited during encoding of items with different subsequent memory fate. Compared to younger adults, older adults’ memory representations were more similar to each other but items that elicited the most similar activity patterns early in the encoding trial were those that were best remembered by older adults. In contrast, young adults’ memory performance benefited from decreased similarity between earlier and later periods in the encoding trials, which might reflect their better success in forming unique memorable mental images of the joint picture–word pair. Our results advance the understanding of the representational properties that give rise to memory quality as well as how these properties change in the course of aging.

We studied oscillatory mechanisms of memory formation in 48 younger and 51 older adults in an intentional associative memory task with cued recall. While older adults showed lower memory performance than young adults, we found subsequent memory effects (SME) in alpha/beta and theta frequency bands in both age groups. Using logistic mixed effect models, we investigated whether interindividual differences in structural integrity of key memory regions could account for interindividual differences in the strength of the SME. Structural integrity of inferior frontal gyrus (IFG) and hippocampus was reduced in older adults. SME in the alpha/beta band were modulated by the cortical thickness of IFG, in line with its hypothesized role for deep semantic elaboration. Importantly, this structure–function relationship did not differ by age group. However, older adults were more frequently represented among the participants with low cortical thickness and consequently weaker SME in the alpha band. Thus, our results suggest that differences in the structural integrity of the IFG contribute not only to interindividual, but also to age differences in memory formation.

Memory consolidation during sleep relies on the precisely timed interaction of rhythmic neural events. Here, we investigate differences in slow oscillations (SO; 0.5–1 Hz), sleep spindles (SP), and their coupling across the adult human lifespan and ask whether observed alterations relate to the ability to retain associative memories across sleep. We demonstrate that older adults do not show the fine-tuned coupling of fast SPs (12.5–16 Hz) to the SO peak present in younger adults but, instead, are characterized most by a slow SP power increase (9–12.5 Hz) at the end of the SO up-state. This slow SP power increase, typical for older adults, coincides with worse memory consolidation in young age already, whereas the tight precision of SO–fast SP coupling promotes memory consolidation across younger and older adults. Crucially, brain integrity in source regions of SO and SP generation, including the medial prefrontal cortex, thalamus, hippocampus and entorhinal cortex, reinforces this beneficial SO–SP coupling in old age. Our results reveal that cognitive functioning is not only determined by maintaining structural brain integrity across the adult lifespan, but also by the preservation of precisely timed neural interactions during sleep that enable the consolidation of declarative memories.

Memory consolidation during sleep relies on the precisely timed interaction of rhythmic neural events. Here, we investigate differences in slow oscillations (SO) and sleep spindles (SP) and their coupling across the adult human lifespan and ask whether observed alterations relate to the ability to retain associative memories across sleep. We demonstrate that the fine-tuned SO–SP coupling that is present in younger adults diffuses with advanced age and shifts both in time and frequency. Crucially, we show that the tight precision of SO–SP coupling promotes memory consolidation in younger and older adults, and that brain integrity in source regions for the generation of SOs and SPs reinforces this beneficial SO–SP coupling in old age. Our results reveal age-related differences in SO–SP coupling in healthy elderly individuals. Furthermore, they broaden our understanding of the conditions and the functional significance of SO–SP coupling across the entire adult lifespan.

Experience can affect human gray matter volume. The behavioral correlates of individual differences in such brain changes are not well understood. In a group of Swedish individuals studying Italian as a foreign language, we investigated associations among time spent studying, acquired vocabulary, baseline performance on memory tasks, and gray matter changes. As a way of studying episodic memory training, the language learning focused on acquiring foreign vocabulary and lasted for 10 weeks. T-1-weighted structural magnetic resonance imaging and cognitive testing were performed before and after the studies. Learning behavior was monitored via participants' use of a smartphone application dedicated to the study of vocabulary. A whole-brain analysis showed larger changes in gray matter structure of the right hippocampus in the experimental group (N = 33) compared to an active control group (N = 23). A first path analyses revealed that time spent studying rather than acquired knowledge significantly predicted change in gray matter structure. However, this association was not significant when adding performance on baseline memory measures into the model, instead only the participants' performance on a short-term memory task with highly similar distractors predicted the change. This measure may tap similar individual difference factors as those involved in gray matter plasticity of the hippocampus.

Multi-scale entropy (MSE) has been recently established as a promising tool for the analysis of the moment-to-moment variability of neural signals. Appealingly, MSE provides a measure of the predictability of neural operations across the multiple time scales on which the brain operates. An important limitation in the application of the MSE to some classes of neural signals is MSE's apparent reliance on long time series. However, this sparse-data limitation in MSE computation could potentially be overcome via MSE estimation across shorter time series that are not necessarily acquired continuously (e.g., in fMRI block-designs). In the present study, using simulated, EEG, and fMRI data, we examined the dependence of the accuracy and precision of MSE estimates on the number of data points per segment and the total number of data segments. As hypothesized, MSE estimation across discontinuous segments was comparably accurate and precise, despite segment length. A key advance of our approach is that it allows the calculation of MSE scales not previously accessible from the native segment lengths. Consequently, our results may permit a far broader range of applications of MSE when gauging moment-to-moment dynamics in sparse and/or discontinuous neurophysiological data typical of many modern cognitive neuroscience study designs.

Higher cognitive functions, such as human perceptual decision making, require information processing and transmission across widespread cortical networks. Temporally synchronized neural firing patterns are advantageous for efficiently representing and transmitting information within and between assemblies. Computational, empirical, and conceptual considerations all lead to the expectation that the informational redundancy of neural firing rates is positively related to their synchronization. Recent theorizing and initial evidence also suggest that the coding of stimulus characteristics and their integration with behavioral goal states require neural interactions across a hierarchy of timescales. However, most studies thus have focused on neural activity in a single frequency range or on a restricted set of brain regions. Here we provide evidence for cooperative spatiotemporal dynamics of slow and fast EEG signals during perceptual decision making at the single-trial level. Participants performed three masked two-choice decision tasks, one each with numerical, verbal, or figural content. Decrements in posterior alpha power (8 - 14 Hz) were paralleled by increments in high-frequency (>30 Hz) signal entropy in trials demanding active sensory processing. Simultaneously, frontocentral theta power (4 - 7 Hz) increased, indicating evidence integration. The coordinated alpha/theta dynamics were tightly linked to decision speed and remarkably similar across tasks, suggesting a domain-general mechanism. In sum, we demonstrate an inverse association between decision-related changes in widespread low-frequency power and local high-frequency entropy. The cooperation among mechanisms captured by these changes enhances the informational density of neural response patterns and qualifies as a neural coding system in the service of perceptual decision making., AuthorCount:6

The individual alpha frequency (IAF) of the human EEG reflects systemic properties of the brain, is highly heritable, and relates to cognitive functioning. Not much is known about the modifiability of IAF by cognitive interventions. We report analyses of resting EEG from a large-scale training study in which healthy younger (2031 years, N=30) and older (6580 years, N=28) adults practiced 12 cognitive tasks for approximate to 100 1-h sessions. EEG was recorded before and after the cognitive training intervention. In both age groups, IAF (and, in a control analysis, alpha amplitude) did not change, despite large gains in cognitive performance. As within-session reliability and test-retest stability were high for both age groups, imprecise measurements cannot account for the findings. In sum, IAF is highly stable in healthy adults up to 80 years, not easily modifiable by cognitive interventions alone, and thus qualifies as a stable neurophysiological trait marker., AuthorCount:6

Some eighty years after the discovery of the human electroencephalogram (EEG) and its dominant rhythm, alpha (similar to 10 Hz), the neurophysiological functions and behavioral correlates of alpha oscillations are still under debate. Similarly, the biological mechanisms contributing to the general factor of intelligence, or g, have been under scrutiny for decades. Individual alpha frequency (IAF), a trait-like parameter of the EEG, has been found to correlate with individual differences in cognitive performance and cognitive abilities. Informed by large-scale theories of neural organization emphasizing the general functional significance of oscillatory activity, the present study replicates and extends these findings by testing the hypothesis that IAF is related to intelligence at the level of g, rather than at the level of specific cognitive abilities. Structural equation modeling allowed us to statistically control for measurement error when estimating the association between IAF and intellectual functioning. In line with our hypothesis, we found a statistically reliable and substantial correlation between IAF and g (r = .40). The magnitude of this correlation did not differ significantly between younger and older adults, and captured all of the covariation between IAF and the cognitive abilities of reasoning, memory, and perceptual speed. The observed association between IAF and g provides a parsimonious explanation for the commonly observed diffuse pattern of correlations between IAF and cognitive performance. We conclude that IAF is a marker of global architectural and functional properties of the human brain., AuthorCount:6