bioRxiv Science⌕ Search

Biology subjects

Lindenberger, U.

Publications and source records attributed to Lindenberger, U..

At least 19 recordsLinked to original sources

Infantile amnesia results from differential memory retrieval in humans

Infantile amnesia, the inability to recall memories from our earliest years, is the most common form of forgetting in mammals. Whether early memories never form, decay, or persist but become inaccessible remains unknown. Here, we investigated the nature of forgetting during the infantile amnesia period by longitudinally testing toddlers aged 18-24 months across the complete memory cycle from encoding, initial retrieval one day later, and delayed retrieval up to six months later, in a novel naturalistic episodic memory paradigm. Computational modelling revealed that forgetting during the infantile amnesia period was heterogeneous. Toddlers were as likely to retain the full memory as to lose it completely, while nearly a quarter retained only part of the memory. Encoding accuracy predicted which toddlers retained the full memory at the test one day later, but not at the delayed test up to six months on. Instead, a retrieval-specific EEG signature predicted complete, but not partial, memory retrieval, distinguishing which toddlers had retained the full memory before their behavioural response. Finally, leveraging the COVID-19 pandemic as a natural experiment, we found that maternal immune activation during pregnancy, as in rodents, alters vulnerability to infantile forgetting in humans. Together, these findings show that early memories formed during the infantile amnesia period are not simply erased but persist in an increasingly inaccessible form, a transformation whose trajectory can be shaped by both the neural retrieval mechanism and the prenatal environment.

neuroscience↗

Genomics of Educational Attainment Across 80 Years of Social and Political Transformation in Germany

Abrupt social and political transformations in twentieth-century Germany may have shifted how polygenic indices relate to educational outcomes across birth cohorts. Following a prespecified analysis plan, we harmonized genomic, educational, and regional data from four German studies, comprising 13,049 individuals born between 1918 and 1995. Polygenic index associations with educational attainment were robust and strengthened modestly across more recent birth cohorts, with no detectable difference between East and West Germany. Associations with intergenerational educational mobility showed no evidence of such strengthening but were stronger in the East than in the West. Polygenic indices were less predictive of educational attainment and educational mobility for women than for men, with no evidence of regional variation. We discuss the methodological limitations of polygenic indices for examining gene-environment interactions, and emphasize that evaluating whether these differences represent progress towards equal educational opportunity requires a normative framework that social science genetics alone cannot supply.

genomics↗

Capturing the developing brain in motion: A practical tutorial for recording mobile EEG in naturally moving children

This tutorial seeks to facilitate the use of mobile electroencephalography (EEG) in young children. Mobile EEG allows researchers to investigate neural correlates of behavioral and cognitive processes in ecologically valid settings. While mobile EEG has been widely adopted in adult research, studies applying it to freely moving children remain scarce. However, investigating neural processes during active behavior and in interaction with movement is indispensable for advancing our understanding of neural correlates of cognitive development in early childhood. Here, we provide a practical tutorial on the collection and preprocessing of mobile EEG data from children. Drawing on experience and data from a large-scale study with toddlers, we summarize key methodological considerations, discuss common challenges and practical recommendations, and present a preprocessing pipeline developed for developmental mobile EEG data. In addition, we provide example EEG datasets from naturally moving 18-20-month-old toddlers. We argue that incorporating mobile EEG into developmental cognitive neuroscience allows researchers to (i) investigate cognitive development in naturalistic environments, (ii) examine associations among bodily movement, neural activity, and behavior, and (iii) study samples that are difficult to reach with stationary research. HighlightsO_LIMobile EEG enables investigation of neural processes during active behavior C_LIO_LIMobile EEG in moving freely children comes with unique methodological challenges C_LIO_LIWe provide practical recommendations for developmental mobile EEG studies C_LIO_LIA dataset and preprocessing pipeline from a toddler mobile EEG study are provided C_LI

neuroscience↗

Developmental Correlates of Epigenetic and Polygenic Indices of Cognition and Educational Attainment from Birth to Young Adulthood

Large-scale genomic studies have identified biomarkers of adult cognitive functioning and educational attainment, yet the developmental pathways connecting these biomarkers to adult outcomes remain unclear. Drawing on four cohorts, we examined the developmental correlates of an epigenetic index of adult cognitive function ( Epigenetic-g) alongside polygenic indices of cognition and education. Epigenetic-g and polygenic indices were uncorrelated and captured distinct variation in childrens cognitive and academic performance. Longitudinal analyses revealed that Epigenetic-g is plastic in early childhood, reaching moderate stability by adolescence, and, unlike polygenic indices, is not related to longitudinal cognitive growth. Twin models indicated that Epigenetic-g captures genetic and unique environmental variation relevant to cognitive and academic achievement that is not identified by current polygenic indices. Epigenetic indices relevant to psychological development can be generated from DNA methylation studies of adults, with most variation in these indices emerging early in life.

genomics↗

Modular functional brain network organization contributes to training-related changes in task switching in children

Cognitive training often aims to improve cognitive skills, but outcomes have been variable in terms of their success. One factor that has been found to predict training outcomes is the degree of modularity of functional brain networks, defined as the extent to which brain regions are more strongly connected to regions within the same functional subnetwork than to regions outside of the subnetwork. Specifically, more modular organization of functional brain networks at baseline has been associated with greater benefits from cognitive training in adults. During childhood, cognitive development is marked by a slow progression towards network integration and segregation, which together contribute to increasing modularity. Thus, network modularity might also be an important predictor of training outcomes in children. To investigate whether individual differences in network modularity predict training outcomes in children, we examined 84 children aged 8 to 11 years who completed nine weeks of either high-intensity task-switching training or high-intensity single-task training. Prior to training, children showed lower network modularity than adults, in line with previously reported developmental changes in network configuration. With training, performance improved, especially in the high-intensity task-switching group. More modular organization of functional brain networks before training was associated with faster improvements in task-switching performance, especially at the beginning of training. These results suggest that more modular functional networks might allow for faster adaptation to training demands in children and thus faster improvements with training. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=180 SRC="FIGDIR/small/708262v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@ac568aorg.highwire.dtl.DTLVardef@658bb4org.highwire.dtl.DTLVardef@b6eb24org.highwire.dtl.DTLVardef@1079a4a_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights- Intensive training improved task-switching performance in children. - Children showed less modular network organization than adults. - More modular networks before training were associated with faster training gains. - Children with more modular networks adapted more quickly to training demands.

neuroscience↗

Distinguishing Lifelong Individual Differences from Divergent Aging Trajectories of Adult Brain Volumes

Individual differences in the volumes of brain structures are often linked to various conditions, including Alzheimers disease, schizophrenia, and overall brain health. However, it remains unclear to what extent these differences reflect individual levels present from young adulthood or diverging aging trajectories from later ages. In this study, we analyze the aging dynamics of the volumes of six brain structures based on magnetic resonance imaging (MRI) scans from a large cross-cohort longitudinal sample of cognitively healthy adults (n = 8,311 with 18,520 MRIs, ages from 18 to 97 years). From general assumptions about structural brain dynamics and measurement noise, a stochastic dynamical model was fitted to the data to estimate both the variability and persistence of structural changes across adulthood. Using this model, we calculated how much of the variance of volumetric differences between individuals can be attributed to stable levels from young adulthood versus systematic changes at older ages, as well as the theoretical sensitivity of longitudinal studies to detect individual differences in change. The findings were as follows: 1) Before age 60 years, inter-individual differences in neuroanatomical volumes almost exclusively reflect stable differences between individuals, while the influence from systematic differences in rate-of-change increases thereafter; up to 50 % of the variation being due to differences in change at 80 years. In contrast, ventricular volume reflects differences in change from early adulthood. 2) Current brain-age models are unlikely to be sensitive to detect differences in aging trajectories. 3) Imaging studies have low reliability in detecting inter-individual brain changes before age 60. After 60 years, the study reliability increases sharply with longer intervals between scans and more modestly with additional intermediate observations. In conclusion, our results reinforce the view that it is critical to distinguish stable early-adulthood levels from systematic differences in change when studying adult brain aging.

neuroscience↗

Vulnerability to memory decline in aging. A mega-analysis of structural brain change.

Brain atrophy is a key factor behind episodic memory loss in aging, but the nature and ubiquity of this relationship remains poorly understood. This study leveraged 13 longitudinal datasets, including 3,737 cognitively healthy adults (10,343 MRI scans; 13,460 memory assessments), to determine whether brain change-memory change associations are more pronounced with age and genetic risk for Alzheimers Disease. Both factors are associated with accelerated brain decline, yet it remains unclear whether memory loss is exacerbated beyond what atrophy alone would predict. Additionally, we assessed whether memory decline aligns with a global pattern of atrophy or stems from distinct regional contributions. Our mega-analysis revealed a nonlinear relationship between memory decline and brain atrophy, primarily affecting individuals with above-average brain structural decline. The associations were stronger in the hippocampus but also spread across diverse cortical and subcortical regions. The associations strengthened with age, reaching moderate associations in participants in their eighties. While APOE {varepsilon}4 carriers exhibited steeper brain and memory loss, genetic risk had no effect on the change-change associations. These findings support the presence of common biological macrostructural substrates underlying memory function in older age which are vulnerable to multiple age-related factors, even in the absence of overt pathological changes.

neuroscience↗

Reliability of structural brain change in cognitively healthy adult samples.

In neuroimaging research, tracking individuals over time is key to understanding the interplay between brain changes and genetic, environmental, or cognitive factors across the lifespan. Yet, the extent to which we can estimate the individual trajectories of brain change over time with precision remains uncertain. In this study, we estimated the reliability of structural brain change in cognitively healthy adults from multiple samples and assessed the influence of follow-up time and number of observations. Estimates of cross-sectional measurement error and brain change variance were obtained using the longitudinal FreeSurfer processing stream. Our findings showed, on average, modest longitudinal reliability with two years of follow-up. Increasing the follow-up time was associated with a substantial increase in longitudinal reliability while the impact of increasing the number of observations was comparatively minor. On average, 2-year follow-up studies require {approx}2.7 and {approx}4.0 times more individuals than designs with follow-ups of 4 and 6 years to achieve comparable statistical power. Subcortical volume exhibited higher longitudinal reliability compared to cortical area, thickness, and volume. The reliability estimates were comparable to those estimated from empirical data. The reliability estimates were affected by both the cohorts age where younger adults had lower reliability of change, and the preprocessing pipeline where the FreeSurfers longitudinal stream was notably superior than the cross-sectional. Suboptimal reliability inflated sample size requirements and compromised the ability to distinguish individual trajectories of brain aging. This study underscores the importance of long-term follow-ups and the need to consider reliability in longitudinal neuroimaging research.

neuroscience↗

Task-Switch Related Reductions in Neural Distinctiveness in Children and Adults: Commonalities and Differences

Goal-directed behavior requires the ability to flexibly switch between task sets with changing environmental demands. Switching between tasks generally comes at the cost of slower and less accurate responses. Compared to adults, children show greater switch costs, presumably reflecting the protracted development of the ability to flexibly update task-set representations. To examine whether the distinctiveness of neural task-set representations is more strongly affected by a task switch in children compared to adults, we examined multi-voxel patterns of fMRI activation in 88 children (8-11 years, 49 girls) and 53 adults (20-30 years, 28 women) during a task-switching paradigm. Using multivariate pattern analysis (MVPA), we investigated whether task-set representations were less distinct on switch than on repeat trials across frontoparietal, cingulo-opercular, and temporo-occipital regions. Children and adults showed lower accuracy and longer response times on switch than on repeat trials, with higher accuracy costs in children. Decoding accuracy across regions was lower on switch than repeat trials, consistent with the notion that switching reduces the distinctiveness of task-set representations. Reliable age differences in switch-related representational distinctiveness reductions were absent, pointing to a remarkable degree of maturity of neural representations of task-relevant information in late childhood. However, we also observed that switch-related reductions in distinctiveness were more highly correlated across frontoparietal and cingulo-opercular regions in children than in adults, potentially reflecting the ongoing specialization of different control networks with respect to the representation of task features. Significance statementThe ability to flexibly switch between tasks enables goal-directed behavior, but is particularly challenging for children, potentially due to protracted development in the ability to represent multiple and overlapping task rules that link stimuli to appropriate responses. We tested this hypothesis by using neuroimaging to measure brain activity during task switching in 8-11-year-olds and adults. Activation patterns in frontal, parietal, and temporal regions could tell us with above-chance accuracy which task a person was performing when the task remained the same, but not when it had switched. Adults showed greater differentiation across regions in terms of switch-related reductions in distinctiveness than children, suggesting that the relevant functional circuity is present but has not yet fully matured by late childhood.

neuroscience↗

Intensive task-switching training and single-task training differentially affect behavioral and neural manifestations of cognitive control in children

The ability to flexibly switch between tasks develops during childhood. Childrens task-switching performance improves with practice, but the underlying processes remain unclear. We used functional magnetic resonance imaging to examine how nine weeks of task-switching training affect performance and task-related activation and functional connectivity. Children (8-11 years) were assigned to one of three groups: intensive task switching (SW; n = 72), intensive single tasking (SI; n = 74), and passive control (n = 41). While mixing costs decreased in both training groups initially, only the SW group maintained these training-related improvements at the end of training. Activation in dorsolateral prefrontal cortex decreased with training, but again only the SW group maintained these activation decreases at the end of training. Condition-specific connectivity increases with task switching became less pronounced with training, especially in the SI group. Lower costs of task switching along with decreased task-related activations suggest increased processing efficiency in frontoparietal regions with training. Intensive task-switching training was associated with sustained changes, possibly facilitated by a greater mismatch between processing supplies and environmental demands. Our findings suggest that experience-dependent changes with intensive task-switching training do not mirror maturational processes but rather facilitate performance via more efficient task processing.

neuroscience↗

Accelerated brain change in healthy adults is associated with genetic risk for Alzheimer's disease and uncovers adult lifespan memory decline

Across healthy adult life our brains undergo gradual structural change in a pattern of atrophy that resembles accelerated brain changes in Alzheimers disease (AD). Here, using four polygenic risk scores for AD (PRS-AD) in a longitudinal adult lifespan sample aged 30 to 89 years (2-7 timepoints), we show that healthy individuals who lose brain volume faster than expected for their age, have a higher genetic AD risk. We first demonstrate PRS-AD associations with change in early Braak regions, namely hippocampus, entorhinal cortex, and amygdala, and find evidence these extend beyond that predicted by APOE genotype. Next, following the hypothesis that brain changes in ageing and AD are largely shared, we performed machine learning classification on brain change trajectories conditional on age in longitudinal AD patient-control data, to obtain a list of AD-accelerated features and model change in these in adult lifespan data. We found PRS-AD was associated with a multivariate marker of accelerated change in many of these features in healthy adults, and that most individuals above [~]50 years of age are on an accelerated change trajectory in AD-accelerated brain regions. Finally, high PRS-AD individuals also high on a multivariate marker of change showed more adult lifespan memory decline, compared to high PRS-AD individuals with less brain change. Our results support a dimensional account linking normal brain ageing with AD, suggesting AD risk genes speed up the shared pattern of ageing- and AD-related neurodegeneration that starts early, occurs along a continuum, and tracks memory change in healthy adults.

neuroscience↗

Broadscale dampening of uncertainty adjustment in the aging brain

0.The ability to prioritize among input features according to relevance enables adaptive behaviors across the human lifespan. However, relevance often remains ambiguous, and such uncertainty increases demands for dynamic control. While both cognitive stability and flexibility decline during healthy ageing, it is unknown whether aging alters how uncertainty impacts perception and decision-making, and if so, via which neural mechanisms. Here, we assess uncertainty adjustment across the adult lifespan (N = 100; cross-sectional) via behavioral modelling and a theoretically informed set of EEG-, fMRI-, and pupil-based signatures. On the group level, older adults show a broad dampening of uncertainty adjustment relative to younger adults. At the individual level, older individuals with more young-like neural responses also showed better maintained cognitive control. Our results highlight neural mechanisms whose maintenance plausibly enables flexible task-set, perception, and decision computations across the adult lifespan.

neuroscience↗

Single-neuron spiking variability in hippocampus dynamically tracks sensory content during memory formation in humans

During memory formation, the hippocampus is presumed to represent the "content" of stimuli, but how it does so is unknown. Using computational modelling and human single-neuron recordings, we show that the more precisely hippocampal spiking variability tracks the composite features of each individual stimulus, the better those stimuli are later remembered. We propose that moment-to-moment spiking variability may provide a new window into how the hippocampus constructs memories from the building blocks of our sensory world.

neuroscience↗

The integrity of dopaminergic and noradrenergic brain regions is associated with different aspects of late-life memory performance

Researchers have identified changes in dopaminergic neuromodulation as playing a key role in adult memory decline. Facilitated by technical advancements, recent research has also implicated noradrenergic neuromodulation in shaping late-life memory performance. However, it is not yet clear whether these two neuromodulators have distinct roles in age-related cognitive changes. Combining longitudinal high-resolution magnetic resonance imaging of the dopaminergic substantia nigra-ventral tegmental area (SN-VTA) and the noradrenergic locus coeruleus (LC) in younger (n = 69) and older adults (n = 251), we found that dopaminergic and noradrenergic integrity are differentially associated with individual differences in memory performance. While LC integrity was related to better episodic memory across several memory tasks, SN-VTA integrity was linked to working memory. Moreover, consistent with their dense interconnection and a largely shared biosynthesis, dopaminergic and noradrenergic brain regions integrity were positively related, and correlated with medial temporal lobe volumes. Longitudinally, we found that older age was associated with more-negative change in SN- VTA and LC integrity (time point 1-time point 2; mean delay [~]1.9 years). Importantly, changes in LC integrity reliably predicted future episodic memory performance (at time point 3). These findings support the feasibility of in-vivo indices for catecholaminergic integrity with potential clinical utility, given the degeneration of both neuromodulatory systems in several age-associated diseases. Moreover, they highlight differential roles of dopaminergic and noradrenergic neuromodulatory nuclei in late-life cognitive decline.

neuroscience↗

Does prefrontal connectivity during task switching help or hinder children's performance?

The ability to flexibly switch between tasks is key for goal-directed behavior and continues to improve across childhood. Childrens task switching difficulties are thought to reflect less efficient engagement of sustained and transient control processes, resulting in lower performance on blocks that intermix tasks (sustained demand) and trials that require a task switch (transient demand). Sustained and transient control processes are associated with frontoparietal regions, which develop throughout childhood and may contribute to task switching development. We examined age differences in the modulation of frontoparietal regions by sustained and transient control demands in children (8-11 years) and adults. Children showed greater performance costs than adults, especially under sustained demand, along with less upregulation of sustained and transient control activation in frontoparietal regions. Compared to adults, children showed increased connectivity between the inferior frontal junction (IFJ) and lateral prefrontal cortex (lPFC) from single to mixed blocks. For children whose sustained activation was less adult-like, increased IFJ-lPFC connectivity was associated with better performance. Children with more adult-like sustained activation showed the inverse effect. These results suggest that individual differences in task switching in later childhood at least partly depend on the recruitment of frontoparietal regions in an adult-like manner.

neuroscience↗

Dynamic regulation of neural variability during working memory reflects dopamine, functional integration, and decision-making

The regulation of moment-to-moment neural variability may permit effective responses to changing cognitive demands. However, the mechanisms that support variability regulation are unknown. In the context of working memory, we leverage the largest available PET and fMRI dataset to jointly consider three lenses through which neural variability regulation could be understood: dopamine capacity, network-level functional integration, and flexible decision processes. We show that with greater working memory load, upregulation of variability was associated with elevated dopamine capacity and heightened functional integration, effects dominantly expressed in the striato-thalamic system rather than cortex. Strikingly, behavioral modeling revealed that working memory load evoked substantial decision biases during evidence accumulation, and those who jointly expressed a more optimal decision bias and higher dopamine capacity were most likely to upregulate striato-thalamic variability under load. We argue that the ability to align striato-thalamic variability to level of demand may be a hallmark of a well-functioning brain.

neuroscience↗

Brain aging differs with cognitive ability regardless of education

Higher general cognitive ability (GCA) is associated with lower risk of neurodegenerative disorders, but neural mechanisms are unknown. GCA could be associated with more cortical tissue, from young age, i.e. brain reserve, or less cortical atrophy in adulthood, i.e. brain maintenance. Controlling for education, we investigated the relative association of GCA with reserve and maintenance of cortical volume, -area and -thickness through the adult lifespan, using multiple longitudinal brain imaging cohorts (n = 3327, 7002 MRI scans, baseline age 20-88 years, followed-up up to 11 years). There were widespread positive relationships between GCA and cortical characteristics (level-level associations). In select regions, higher baseline GCA was associated with less atrophy over time (level-change associations). Relationships remained when controlling for polygenic scores for both GCA and education. Our findings suggest that higher GCA is associated with cortical volumes by both brain reserve and -maintenance mechanisms through the adult lifespan.

neuroscience↗

Vamos en bici: Study protocol of an investigation of cognitive and neural changes following language training, physical exercise training, or a combination of both

As the relative number of elderly people as well as the average life expectancy increases, identifying potential means to alter the ongoing trajectory of aging and specifically the trajectory of cognitive performance is of great importance. Some modifiable lifestyle factors, such as physical and cognitive activity, have shown positive effects on cognition and brain structure, and the combination of the two might even show a boosted, interactive effect. In this study protocol, we describe in detail our data which was acquired to explore how cognitive stimulation in the form of acquiring a new language, physical exercise on stationary bikes or the combination of the two interventions affect brain structure, cognitive performance, and psychosocial functioning. One-hundred and forty-two older healthy adults (63-78 years) were randomly assigned to one of four six-month intervention programs, comprising (a) foreign language learning, (b) physical exercise training on a bicycle ergometer, (c) a combination of language learning and physical exercise, or (d) a book club (serving as an active control condition). We collected a rich neuroimaging data set, comprising T1-weighted structural, resting state functional, high resolution hippocampal, myelin water fraction, diffusion-weighted, arterial spin labeling, and multi-parameter images. Using a cognitive battery, we collected data from the domains of episodic memory, working memory, perceptual speed, and fluid intelligence. We performed comprehensive physical assessments including cardiopulmonary exercise testing, and additionally collected data on psychosocial functioning (e.g., well-being, perceived stress, control beliefs). We assume that physical activity boosts brain plasticity per se by inducing structural and neurochemical changes in brain regions that are important for learning and memory and therefore may facilitate the effects of cognitive training. (269 words)

neuroscience↗