Michael R. Waldmann

Georg-Elias-Müller-Institut für Psychologie, Universität Göttingen
Abteilung Kognitionswissenschaften und Entscheidungspsychologie (Cognitive and Decision Sciences)

Index Michael R. Waldmann

Personen
People

Forschung
Research

Lehre
Courses

Contact Information

Department of Psychology; University of Göttingen; Gosslerstr. 14; 37073 Göttingen; GERMANY; Phone: +49-551-393784; Fax: +49-551-393656
michael.waldmann@bio.uni-goettingen.de;
www.psych.uni-goettingen.de/abt/1/waldmann/

Secretary
Birgit Bergmann-Bryant
bbergma@uni-goettingen.de
Phone: +49-551-393634
Fax: +49-551-393656

Biographical Sketch

1981	Diploma in psychology from the University of Munich
1982-87	Graduate student at the Max Planck Institute for Psychological Research, Munich
1988	Ph.D. at the University of Munich
1987-94	Teaching and research positions at the Universities of Frankfurt and Tübingen
1988-90	Postdoctoral research at the University of California, Los Angeles (UCLA); collaboration with Keith Holyoak
1995	Habilitation at the University of Tübingen
1994-98	Senior research scientist at the Max Planck Institute for Psychological Research [Area: 'Behavioral and cognitive development']
1996	Early career research award from the German Society for Psychology ['Charlotte- und Karl-Bühler-Preis']
1998	Professor of Psychology (C3) at the University of Göttingen
2003, 2005	Visiting Scholar at the Department of Psychology, University of California, Los Angeles (UCLA)
since 2002	Chair of the Department of Psychology at the University of Göttingen
since 2005	Professor of Psychology (W3) at the University of Göttingen
2007-2008	Visiting Scholar at the Department of Brain and Cognitive Sciences, MIT (Sept.-Oct.), and the Department of Psychology, UCLA (Nov.-Feb.)

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Current Research Projects

Causal learning

The focus of our research is on higher-level cognitive processes (learning, reasoning, categorization, memory, judgment, decision making). In particular, we are interested in how causal knowledge is acquired, represented, and used. In several projects we are conducting experimental studies that investigate the role of causality in learning, reasoning, categorization, moral judgments, and decision making. We are also interested in the neural basis of causal versus associative processes and in comparative neuroscience.

Current projects:

Causal Bayes models as psychological theories of learning, reasoning, and decision making
Seeing versus doing: Two modes of accessing causal knowledge
Competence vs. performance in causal learning
Causal models and sensitivity to base rates
Categorization and inductive learning
Access to causal semantic memory
Hypothesis testing and logical reasoning
Causal models and bioethical intuitions: Studies on the trolley problem
Rational models of causal category formation (with J. Tenenbaum, MIT)
Neural basis of causality (fMRI studies)(with D. Fenker, University of Magdeburg)
Causal reasoning in rats: Seeing vs. doing (with A. Blaisdell, UCLA)
Causal learning and base rate sensitivity (with U. Reips, University of Zürich)
Causal learning in children (with A. Weber, University for Applied Sciences, Würzburg)

Current external collaborators: Aaron Blaisdell , UCLA; Daniela Fenker , University of Magdeburg; Ulf-Dietrich Reips , University of Zürich; Josh Tenenbaum , MIT; Angelika Weber, University of Applied Sciences, Würzburg

Current research grants
Causal Bayes nets as psychological models of reasoning [DFG project; since 2005]
Categorization and inductive learning [DFG project; since 2002, extended 2005]

Current Ph. D. students
Ralf Mayrhofer

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Teaching

I currently offer courses in the areas of learning, motivation, emotion, judgment and decision making, causal thinking, experimental designs, structural equation modeling (LISREL), the cognitve neuroscience of learning, and neural network modeling.

I am also offering lectures on the neuroscience of memory and learning within the International MSc/PhD Program in the Neurosciences, Göttingen, and the center for systems neuroscience (ZNV), Göttingen. Furthermore, I am a member of the interdisciplinary Center of Statistics and the Graduate Program for Applied Statistics and Empirical Methods, Göttingen.

For further comments on current classes and class materials, see our local course page [German].

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Selected Publications

Meder, B., Gerstenberg, T., Hagmayer, Y., & Waldmann, M. R. (in press). Observing and intervening: Rational and heuristic models of causal decision making. Open Psychology Journal. [Abstract | Full text: PDF-526kb]

Fenker, D. B., Schoenfeld, M. A., Waldmann, M. R., Schuetze, H., Heinze, H.-J., & Duezel, E. (in press). 'Virus and epidemic': Causal knowledge activates prediction error circuitry. Journal of Cognitive Neuroscience. [Abstract | Full text: PDF-291kb]

Waldmann, M. R. (in press). Causal reasoning. In B. Glatzeder, V. Goel & A. v. Müller (Eds.), Perspectives on thinking. Berlin, Heidelberg: Springer Verlag.

Waldmann, M. R., Meder, B., von Sydow, M., & Hagmayer, Y. (2009). The tight coupling between category and causal learning. Cognitive Processing, published online. [Abstract | Full text: PDF-1017kb]

Meder, B., Mayrhofer, R., & Waldmann, M. R. (2009). A rational model of elemental diagnostic inference. In N. Taatgen, H. van Rijn, L. Schomaker & J. Nerbonne (Eds.), Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society (pp. 2176-2181). Austin, TX: Cognitive Science Society.[Abstract | Full text: PDF-692kb]

Griffiths, O., Mayrhofer, R., Nagel, J., & Waldmann, M. R. (2009). Causal schema-based inductive reasoning. In N. Taatgen, H. van Rijn, L. Schomaker & J. Nerbonne (Eds.), Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society (pp. 691-696). Austin, TX: Cognitive Science Society.[Abstract | Full text: PDF-172kb]

Blaisdell, A. P., Leising, K. J., Stahlman, W. D., & Waldmann, M. R. (2009). Rats distinguish between absence of events and lack of information in sensory preconditioning. International Journal of Comparative Psychology, 22, 1-18. [Abstract | Full text: PDF-125kb]

Meder, B., Hagmayer, Y., & Waldmann, M. R. (2009). The role of learning data in causal reasoning about observations and interventions. Memory & Cognition, 37, 249-264.[Abstract | Full text: PDF-513kb]

Mayrhofer, R., Goodman, N. D., Waldmann, M. R., & Tenenbaum, J. B. (2008). Structured correlation from the causal background. In Proceedings of the Thirtieth Annual Conference of the Cognitive Science Society (pp. 303-308). [Abstract | Full text: PDF-524kb]]