Lifespan Psychology

Founded in 1981 by the late Paul B. Baltes, the Center for Lifespan Psychology (LIP) at the Max Planck Institute for Human Development has helped to establish lifespan psychology as a distinct conceptual approach within developmental psychology. Since 2004, the Center has extended its research program into developmental behavioral neuroscience. Work at the Center is guided by three propositions:

to study lifespan changes in behavior as interactions among maturation, learning, and senescence;
to develop theories and methods that integrate empirical evidence across domains of functioning, timescales, as well as behavioral and neural levels of analysis;
to identify mechanisms of development by exploring age-graded differences in plasticity.

The Center continues to pay special attention to the age periods of late adulthood and old age, which offer unique opportunities for innovation, both in theory and practice. At the same time, it has continuously increased its research on behavioral development during earlier periods of life.

Research Report on the Center for Lifespan Psychology

A Philosopher of the Enlightenment Era: Tetens

"But ... its eminent modifiability, and its predisposition to self-initiated action, may it develop little or much, and may it differ in amount between different individuals, is among the immutable features of humankind, which can be found whereever humans exist."

Johann Nicolaus Tetens (1736-1807), philosopher of the Enlightenment Era

The Center's Projects

The Center for Lifespan Psychology's eight projects follow its guiding propositions and examine different facets of human development across the lifespan. Further information is available under Projects.

Selected Recent Publications

Jacobucci, R., Brandmaier, A. M., & Kievit, R. A. (in press). A practical guide to variable selection in structural equation models with regularized MIMIC models. Advances in Methods and Practices in Psychological Science.

Muehlroth, B. E., Sander, M. C., Fandakova, Y., Grandy, T. H., Rasch, B., Shing, Y. L., & Werkle-Bergner, M. (in press). Precise slow oscillation-spindle coupling promotes memory consolidation in younger and older adults. Scientific Reports.

Tucker-Drob, E. M., Brandmaier, A. M., & Lindenberger, U. (in press). Coupled cognitive changes in adulthood: A meta-analysis. Psychological Bulletin.

Voelkle, M. C., Gische, C., Driver, C. C., & Lindenberger, U. (in press). The role of time in the quest for understanding psychological mechanisms. Multivariate Behavioral Research.

Brandmaier, A. M., Driver, C. C., & Voelkle, M. C. (2018). Recursive partitioning in continuous time analysis. In K. van Montfort, J. H. L. Oud, & M. C. Voelkle (Eds.), Continuous time modeling in the behavioral and related sciences (pp. 259–282). Cham: Springer.

Brandmaier, A. M., von Oertzen, T., Ghisletta, P., Lindenberger, U., & Hertzog, C. (2018). Precision, reliability, and effect size of slope variance in latent growth curve models: Implications for statistical power analysis. Frontiers in Psychology, 9:294. https://doi.org/10.3389/fpsyg.2018.00294

Brandmaier, A. M., Wenger, E., Bodammer, N. C., Kühn, S., Raz, N., & Lindenberger, U. (2018). Assessing reliability in neuroimaging research through intra-class effect decomposition (ICED). eLife, 7:e35718. https://doi.org/10.7554/eLife.35718

Cabeza, R., Albert, M., Belleville, S., Craik, F. I. M., Duarte, A., ... Lindenberger, U., ... Rajah, M. N. (2018). Maintenance, reserve and compensation: the cognitive neuroscience of healthy ageing. Nature Reviews Neuroscience, 19, 701–710. https://doi.org/10.1038/s41583-018-0068-2

Driver, C. C., & Voelkle, M. C. (2018). Hierarchical Bayesian continuous time dynamic modeling. Psychological Methods, 23, 774–799. https://doi.org/10.1037/met0000168

Düzel, S., & Gerstorf, D. (Eds.). (2018). Special issue: Future time perspectives. GeroPsych, 31(3).

Fandakova, Y., Sander, M. C., Grandy, T. H., Cabeza, R., Werkle-Bergner, M., & Shing, Y. L. (2018). Age differences in false memory: The importance of retrieval monitoring processes and their modulation by memory quality. Psychology and Aging, 33, 119–133. https://doi.org/10.1037/pag0000212

Garrett, D. D., Epp, S. M., Perry, A., & Lindenberger, U. (2018). Local temporal variability reflects functional integration in the human brain. NeuroImage, 183, 776–787. https://doi.org/10.1016/j.neuroimage.2018.08.019

Ghisletta, P., Burra, E. J., Aichele, S., Lindenberger, U., & Schmiedek, F. (2018). Age differences in day-to-day speed-accuracy tradeoffs: Results from the COGITO study. Multivariate Behavioral Research. Advance online publication. https://doi.org/10.1080/00273171.2018.1463194

Keresztes, A., Ngo, C. T., Lindenberger, U., Werkle-Bergner, M., & Newcombe, N. S. (2018). Hippocampal maturation drives memory from generalization to specificity. Trends in Cognitive Sciences, 22, 676–686. https://doi.org/10.1016/j.tics.2018.05.004

Kievit, R. A., Brandmaier, A. M., Ziegler, G., van Harmelen, A.-L., de Mooij, S. M. M., … Lindenberger, U., & Dolan, R. J. (2018). Developmental cognitive neuroscience using latent change score models: A tutorial and applications. Developmental Cognitive Neuroscience, 33, 99–117. https://doi.org/10.1016/j.dcn.2017.11.007

Köhncke, Y., Papenberg, G., Jonasson, L., Karalija, N., Wåhlin, A., ... Lindenberger, U., & Lövdén, M. (2018). Self-rated intensity of habitual physical activities is positively associated with dopamine D2/3 receptor availability and cognition. NeuroImage, 181, 605–616. https://doi.org/10.1016/j.neuroimage.2018.07.036

Lindenberger, U. (2018). Plasticity beyond early development: Hypotheses and questions. In A. A. Benasich & U. Ribary (Eds.), Emergent brain dynamics: Prebirth to adolescence (pp. 207–223). Cambridge, MA: MIT Press

Lövdén, M., Karalija, N., Andersson, M., Wåhlin, A., ... Köhncke, Y., ... Garrett, D. D., ... Lindenberger, U. (2018). Latent-profile analysis reveals behavioral and brain correlates of dopamine-cognition associations. Cerebral Cortex, 28, 3894–3907. https://doi.org/10.1093/cercor/bhx253

Müller, V., Delius, J. A. M., & Lindenberger, U. (2018). Complex networks emerging during choir singing. Annals of the New York Academy of Sciences, 1431, 85–101. https://doi.org/10.1111/nyas.13940

Müller, V., Sänger, J., & Lindenberger, U. (2018). Hyperbrain network properties of guitarists playing in quartet. Annals of the New York Academy of Sciences, 1423, 198–210. https://doi.org/10.1111/nyas.13656

Raffington, L., Prindle, J., & Shing, Y. L. (2018). Income gains predict cognition longitudinally throughout later childhood in poor children. Developmental Psychology, 54, 1232–1243. https://doi.org/10.1037/dev0000529

Salami, A., Garrett, D., Wahlin, A., Rieckmann, A., , ... Karalija, N., ... Lindenberger, U., ... Nyberg, L. (2018). Dopamine D2/3 binding potential modulates neural signatures of working memory in a load-dependent fashion. Journal of Neuroscience. Advance online publication. https://doi.org/10.1523/JNEUROSCI.1493-18.2018

Salami, A., Rieckmann, A., Karalija, N., ... Papenberg, G., Garrett, D. D., ... Lindenberger, U., ... Nyberg, L. (2018). Neurocognitive profiles of healthy older adults with working-memory dysfunction. Cerebral Cortex. Advance online publication. https://doi.org/10.1093/cercor/bhy062

Schneider, W., & Lindenberger, U. (Eds.). (2018). Entwicklungspsychologie (8th compl. rev. ed.). Weinheim: Beltz.

Selmeczy, D., Fandakova, Y., Grimm, K. J., Bunge, S. A., & Ghetti, S. (2018). Longitudinal trajectories of hippocampal and prefrontal contributions to episodic retrieval: Effects of age and puberty. Developmental Cognitive Neuroscience. Advance online publication. https://doi.org/10.1016/j.dcn.2018.10.003

Yuan, P., Voelkle, M. C., & Raz, N. (2018). Fluid intelligence and gross structural properties of the cerebral cortex in middle-aged and older adults: A multi-occasion longitudinal study. NeuroImage, 172, 21–30. https://doi.org/10.1016/j.neuroimage.2018.01.032

Kühn, S., Düzel, S., Colzato, L., Norman, K., ... Brandmaier, A. M., Lindenberger, U., & Widaman, K. F. (2017). Food for thought: Association between dietary tyrosine and cognitive performance in younger and older adults. Psychological Research. Advance online publication. https://doi.org/10.1007/s00426-017-0957-4

Max Planck UCL Centre for Computational Psychiatry and Ageing Research

Cooperation With University College London (UCL)

The Max Planck UCL Centre for Computational Psychiatry and Ageing Research was launched in April 2014. It is based on an initiative by scientists from the Max Planck Society and UCL targeting the development and application of computational methods that reorganize and improve our understanding of mental illness and behavioral aging.

Further information

Contact

Director:

Ulman Lindenberger

seklindenberger [at] mpib-berlin [dot] mpg [dot] de

Research Report

The Institute's Research Report provides more information on the Center for Lifespan Psychology.

Research Report 2014-2016: LIP

New

New edition of textbook on developmental psychology published.
Further information (in German)

IMPRS LIFE & COMP2PSYCH

The Center for Lifespan Psychology is involved in the following graduate programs of the Max Planck Society:

Lifebrain

The Berlin Aging Studies BASE and BASE-II are participating in Lifebrain, an EU funded project. It integrates data from 6000 participants in 11 European neuroimaging studies carried out in 7 countries.

Website: www.lifebrain.uio.no

Walhovd, K. B., Fjell, A. M., Westerhausen, R., Nyberg, L., Ebmeier, K. P., Lindenberger, U., ... for Lifebrain Consortium. (2018). Healthy minds from 0–100 years: Optimising the use of European brain imaging cohorts ("Lifebrain"). European Psychiatry, 50, 47–56. https://doi.org/ 10.1016/j.eurpsy.2017.12.006

In Memoriam

Paul B. Baltes
(1939–2006)

1980–2004 Director of the Center for Lifespan Psychology