Elisabeth Wenger

Structural brain plasticity in adult learning and development

Recent research using magnetic resonance imaging has documented changes in the adult human brains grey matter structure induced by alterations in experiential demands. We review this research and relate it to models of brain plasticity from related strands of research, such as work on animal models. This allows us to generate recommendations and predictions for future research that may advance the understanding of the function, sequential progression, and microstructural nature of experience-dependent changes in regional brain volumes. Informed by recent evidence on adult age differences in structural brain plasticity, we show how understanding learning-related changes in human brain structure can expand our knowledge about adult development and aging. We hope that this review will promote research on the mechanisms regulating experience-dependent structural plasticity of the adult human brain.

Comparing Manual and Automatic Segmentation of Hippocampal Volumes: Reliability and Validity Issues in Younger and Older Brains

We compared hippocampal volume measures obtained by manual tracing to automatic segmentation with FreeSurfer in 44 younger (20–30 years) and 47 older (60–70 years) adults, each measured with magnetic resonance imaging (MRI) over three successive time points, separated by four months. Retest correlations over time were very high for both manual and FreeSurfer segmentations. With FreeSurfer, correlations over time were significantly lower in the older than in the younger age group, which was not the case with manual segmentation. Pearson correlations between manual and FreeSurfer estimates were sufficiently high, numerically even higher in the younger group, whereas intra‐class correlation coefficient (ICC) estimates were lower in the younger than in the older group. FreeSurfer yielded higher volume estimates than manual segmentation, particularly in the younger age group. Importantly, FreeSurfer consistently overestimated hippocampal volumes independently of manually assessed volume in the younger age group, but overestimated larger volumes in the older age group to a less extent, introducing a systematic age bias in the data. Age differences in hippocampal volumes were significant with FreeSurfer, but not with manual tracing. Manual tracing resulted in a significant difference between left and right hippocampus (right > left), whereas this asymmetry effect was considerably smaller with FreeSurfer estimates. We conclude that FreeSurfer constitutes a feasible method to assess differences in hippocampal volume in young adults. FreeSurfer estimates in older age groups should, however, be interpreted with care until the automatic segmentation pipeline has been further optimized to increase validity and reliability in this age group. Hum Brain Mapp 35:4236–4248, 2014.

Cortical thickness changes following spatial navigation training in adulthood and aging

A widespread network involving cortical and subcortical brain structures forms the neural substrate of human spatial navigation. Most studies investigating plasticity of this network have focused on the hippocampus. Here, we investigate age differences in cortical thickness changes evoked by four months of spatial navigation training in 91 men aged 20-30 or 60-70 years. Cortical thickness was automatically measured before, immediately after, and four months after termination of training. Younger as well as older navigators evidenced large improvements in navigation performance that were partly maintained after termination of training. Importantly, training-related cortical thickening in left precuneus and paracentral lobule were observed in young navigators only. Thus, spatial navigation training appears to affect cortical brain structure of young adults, but there is reduced potential for experience-dependent cortical alterations in old age.

The dynamics of change in striatal activity following updating training

Increases in striatal activity have been suggested to mediate training‐related improvements in working‐memory ability. We investigated the temporal dynamics of changes in task‐related brain activity following training of working memory. Participants in an experimental group and an active control group, trained on easier tasks of a constant difficulty in shorter sessions than the experimental group, were measured before, after about 1 week, and after more than 50 days of training. In the experimental group an initial increase of working‐memory related activity in the functionally defined right striatum and anatomically defined right and left putamen was followed by decreases, resulting in an inverted u‐shape function that relates activity to training over time. Activity increases in the striatum developed slower in the active control group, observed at the second posttest after more than 50 days of training. In the functionally defined left striatum, initial activity increases were maintained after more extensive training and the pattern was similar for the two groups. These results shed new light on the relation between activity in the striatum (especially the putamen) and the effects of working memory training, and illustrate the importance of multiple measurements for interpreting effects of training on regional brain activity. Hum Brain Mapp, 2013.

Contribution of neuroinflammation and immunity to brain aging and the mitigating effects of physical and cognitive interventions

It is widely accepted that the brain and the immune system continuously interact during normal as well as pathological functioning. Human aging is commonly accompanied by low-grade inflammation in both the immune and central nervous systems, thought to contribute to many age-related diseases. This review of the current literature focuses first on the normal neuroimmune interactions occurring in the brain, which promote learning, memory and neuroplasticity. Further, we discuss the protective and dynamic role of barriers to neuroimmune interactions, which have become clearer with the recent discovery of the meningeal lymphatic system. Next, we consider age-related changes of the immune system and possible deleterious influences of immunosenescence and low-grade inflammation (inflammaging) on neurodegenerative processes in the normally aging brain. We survey the major immunomodulators and neuroregulators in the aging brain and their highly tuned dynamic and reciprocal interactions. Finally, we consider our current understanding of how physical activity, as well as a combination of physical and cognitive interventions, may mediate anti-inflammatory effects and thus positively impact brain aging.

Plasticity of brain and cognition in older adults

Aging is typically related to changes in brain and cognition, but the aging process is heterogeneous and differs between individuals. Recent research has started investigating the influence of cognitive and physical training on cognitive performance, functional brain activity, and brain structure in old age. The functional relevance of neural changes and the interactions among these changes following interventions is still a matter of debate. Here we selectively review research on structural and functional brain correlates of training-induced performance changes in healthy older adults and present exemplary longitudinal intervention studies sorted by the type of training applied (i.e., strategy-based training, process-specific training, and physical exercise). Although many training studies have been conducted recently, within each task domain, the number of studies that used comparable methods and techniques to assess behavioral and neural changes is limited. We suggest that future studies should include a multimodal approach to enhance the understanding of the relation between different levels of brain changes in aging and those changes that result from training. Investigating inter-individual differences in intervention-induced behavioral and neuronal changes would provide more information about who would benefit from a specific intervention and why. In addition, a more systematic examination of the time course of training-related structural and functional changes would improve the current level of knowledge about how learning is implemented in the brain and facilitate our understanding of contradictory results.

Resting-state fMRI correlations: From link-wise unreliability to whole brain stability

&NA; The functional architecture of spontaneous BOLD fluctuations has been characterized in detail by numerous studies, demonstrating its potential relevance as a biomarker. However, the systematic investigation of its consistency is still in its infancy. Here, we analyze within‐ and between‐subject variability and test‐retest reliability of resting‐state functional connectivity (FC) in a unique data set comprising multiple fMRI scans (42) from 5 subjects, and 50 single scans from 50 subjects. We adopt a statistical framework that enables us to identify different sources of variability in FC. We show that the low reliability of single links can be significantly improved by using multiple scans per subject. Moreover, in contrast to earlier studies, we show that spatial heterogeneity in FC reliability is not significant. Finally, we demonstrate that despite the low reliability of individual links, the information carried by the whole‐brain FC matrix is robust and can be used as a functional fingerprint to identify individual subjects from the population.

Expansion and Renormalization of Human Brain Structure During Skill Acquisition

Research on human brain changes during skill acquisition has revealed brain volume expansion in task-relevant areas. However, the large number of skills that humans acquire during ontogeny militates against plasticity as a perpetual process of volume growth. Building on animal models and available theories, we promote the expansion-renormalization model for plastic changes in humans. The model predicts an initial increase of gray matter structure, potentially reflecting growth of neural resources like neurons, synapses, and glial cells, which is followed by a selection process operating on this new tissue leading to a complete or partial return to baseline of the overall volume after selection has ended. The model sheds new light on available evidence and current debates and fosters the search for mechanistic explanations.

Repeated Structural Imaging Reveals Nonlinear Progression of Experience-Dependent Volume Changes in Human Motor Cortex

&NA; Evidence for experience‐dependent structural brain change in adult humans is accumulating. However, its time course is not well understood, as intervention studies typically consist of only 2 imaging sessions (before vs. after training). We acquired up to 18 structural magnetic resonance images over a 7‐week period while 15 right‐handed participants practiced left‐hand writing and drawing. After 4 weeks, we observed increases in gray matter of both left and right primary motor cortices relative to a control group; 3 weeks later, these differences were no longer reliable. Time‐series analyses revealed that gray matter in the primary motor cortices expanded during the first 4 weeks and then partially renormalized, in particular in the right hemisphere, despite continued practice and increasing task proficiency. Similar patterns of expansion followed by partial renormalization are also found in synaptogenesis, cortical map plasticity, and maturation, and may qualify as a general principle of structural plasticity. Research on human brain plasticity needs to encompass more than 2 measurement occasions to capture expansion and potential renormalization processes over time.

Corrigendum to "Resting-state fMRI correlations: From link-wise unreliability to whole brain stability" [NeuroImage, 157 (2017 Aug 15), 250-262. doi:10.1016/j.neuroimage.2017.06.006]

a Universitat Pompeu Fabra, Theoretical and Computational Neuroscience, Center for Brain and Cognition, Roc Boronat, 138, 08018 Barcelona, Spain b Max Planck Institute for Human Development, Center for Lifespan Psychology, Lentzeallee 94, 14195 Berlin, Germany c University Clinic Hamburg-Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246 Hamburg, Germany d Department of Psychology, Lund University, Box 117, 221 00 Lund, Sweden e Department of Psychology, Humboldt Universit€ at zu Berlin, Unter Den Linden 6, 10099 Berlin, Germany f Bernstein Center for Computational Neuroscience Berlin, Philippstr. 13 Haus 6, 10115 Berlin, Germany g Instituci o Catalana de Recerca I Estudis Avançats (ICREA), Universitat Pompeu Fabra, Theoretical and Computational Neuroscience, Center for Brain and Cognition, Roc Boronat, 138, 08018 Barcelona, Spain The authors regret “Missing figures in the supplementary information and missing one author: Prof. Ulman Lindenberger (Max Planck Institute