IMBB Institute for Mind, Brain and Behavior

• Aufbau von Forschungsmodulen in der Lehre: Kausale Inferenz, Kognitive Neurowissenschaften, Wahrnehmung und Psychophysik
• Eigene Forschungsschwerpunkte: Komparative evolutionäre Neuroanatomie, Computational Psychiatry, Metakognition, Auditive Kognition, Lernen, Individuelle Unterschiede im Erleben und Verhalten
• Forschungsinfrastruktur: Experimentallabor für Psychoakustik, Eye-Tracking, Histologielabor, Konfokalmikroskop
• Methoden: Komputationale Modellierung, Psychophysik, Bayes Statistik, Maschinelles Lernen, (f)MRT,Histologie, Strukturgleichungsmodelle
• Repräsentation der Fächer Allgemeine, Biologische und Mathematische Psychologie, Quantitative Methoden und Neurowissenschaften in nationalen/internationalen Konsortien, Fachgesellschaften und Institutionen

Neurowissenschaften - Psychologische Grundlagenforschung - Statistik und Kognitive Modellierung

• Alterung und Degeneration neuronaler Netzwerke (C. elegans)
• Visuelle und Auditive Wahrnehmung, Psychophysik
• Kognition, Metakognition, Kognitive Modellierung, Bildgebung
• Assoziatives und affektives Lernen, kausale Schlüsse, Entscheiden​
• Messung, Entwicklung und Konsequenzen von Persönlichkeit
• Evolution des Gehirns bei Säugern
• Statistische Methoden

Prof. Dr. Karl Emanuel Busch
Professur für Physiologie 
Alterung und Degeneration neuronaler Netzwerke in C. Elegans

Prof. Dr. Michael Grosz
Professur für Psychologische Diagnostik
Messung, Entwicklung und Konsequenzen von Persönlichkeit

Prof. Dr. habil. Matthias Guggenmos
Professur für Komputationale Kognitive Neurowissenschaften
Wahrnehmung, Metakognition, Kognitive Modellierung, Bildgebung

Prof. Dr. habil. Florian Kattner
Professur für Allgemeine Psychologie
Auditive Kognition, Assoziatives Lernen, Psychophysik

Prof. Dr. Björn Meder
Professur für Allgemeine Psychologie
Lernen, kausale Schlüsse, Entscheiden

Prof. Dr. Nina Patzke
Professur für Neuroanatomie
Evolution des Gehirns bei Säugern

Prof. Dr. Daniel Schad
Professur für Quantitative Methoden
Statistische Methoden, affektive Lernprozesse

AG Auditive Kognition, Assoziatives Lernen, Psychophysik

• Samuel Conrad
• Mitra Hassanzadeh (ab April 2023)

AG Statistische Methoden, affektive Lernprozesse

• Laura A. Wirth

AG Messung, Entwicklung und Konsequenzen von Persönlichkeit

• Richard Rau

    2023

• Adams, Z., Osman, M., Bechlivanidis, C., & Meder, B. (2023). (Why) Is misinformation a problem? Perspectives on Psychological Science. Advance online publication. https://journals.sagepub.com/doi/10.1177/17456916221141344
• Kattner, F., Fischer, M., Caling, A., Cremona, S., Ihle, A., Hodgson, T., & Föcker, J. (2023). The disruptive effects of changing-state sound and emotional prosody on verbal short-term memory in blind, visually impaired, and sighted listeners. Journal of Cognitive Psychology. doi: 10.1080/20445911.2023.2186771
• Liu, S., Rabovsky, M., & Schad, D. J. (2023). Spontaneous mind wandering impairs model-based decision making. PloS one, 18(1), e0279532. https://doi.org/10.1371/journal.pone.0279532
• Liu, S., Li, R., Wegner, L., Huang, C., Haucke, M. N., Schad, D. J., Zhao, M., & Heinzel, S. (2023). High-mind wandering correlates with high risk for problematic alcohol use in China and Germany. European archives of psychiatry and clinical neuroscience, 1–7. Advance online publication. https://doi.org/10.1007/s00406-023-01555-4
• Ptasczynski, L. E., Steinecker, I., Sterzer, P., & Guggenmos, M. (2022). The value of confidence: Confidence prediction errors drive value-based learning in the absence of external feedback. PLoS computational biology, 18(10), e1010580. https://doi.org/10.1371/journal.pcbi.1010580
• van Doorn, J., …, Schad, D.J., …, Aust, F. (2023). Bayes Factors for Mixed Models: a Discussion. Computational Brain & Behavior, doi: 10.1007/s42113-022-00160-3

    2022

• Bağci, B., Düsmez, S., Zorlu, N., Bahtiyar, G., Isikli, S., Bayrakci, A., Heinz, A., Schad, D. J., & Sebold, M. (2022). Computational analysis of probabilistic reversal learning deficits in male subjects with alcohol use disorder. Frontiers in psychiatry, 13, 960238. https://doi.org/10.3389/fpsyt.2022.960238
• Eckert, A. L., Gounitski, Y., Guggenmos, M., & Sterzer, P. (2022). Cross-Modality Evidence for Reduced Choice History Biases in Psychosis-Prone Individuals. Schizophrenia bulletin, sbac168. Advance online publication. https://doi.org/10.1093/schbul/sbac168
• Ellermeier, W., Kattner, F., & Raum, A. (2022). Correction to: Cross‑modal commutativity of magnitude productions. Attention, Perception, & Psychophysics, 84, 322-323. doi: 10.3758/s13414-021-02385-z
• Guggenmos M. (2022). Reverse engineering of metacognition. eLife, 11, e75420. https://doi.org/10.7554/eLife.75420
• Kattner, F., & Bryce, D. (2022). Attentional control and metacognitive monitoring of the effects of different types of task-irrelevant sound on serial recall. Journal of experimental psychology. Human perception and performance, 48(2), 139–158. https://doi.org/10.1037/xhp0000982
• Kattner, F., & Gast, A. (2022). Scaling preferences using probabilistic choice models: is there a ratio-scale representation of subjective liking?. Psychological research, 10.1007/s00426-022-01775-8. Advance online publication. https://doi.org/10.1007/s00426-022-01775-8
• Kattner, F., Hanl, S., Paul, L., & Ellermeier, W. (2022). Task-specific auditory distraction in serial recall and mental arithmetic. Memory & cognition, 1–22. Advance online publication. https://doi.org/10.3758/s13421-022-01363-6
• Kattner, F., Richardson, B. H., & Marsh, J. E. (2022). The benefit of foreknowledge in auditory distraction depends on the intelligibility of pre-exposed speech. Auditory Perception & Cognition, 5(3-4), 151-168. doi: 10.1080/25742442.2022.2089525
• Li, Q., Marcu, D. C., Dear, P. H., & Busch, K. E. (2022). Aerotaxis Assay in Caenorhabditis elegans to Study Behavioral Plasticity. Bio-protocol, 12(16), e4492. https://doi.org/10.21769/BioProtoc.4492
• Magrabi, A., Beck, A., Schad, D.J., Lett, T.A., Stoppel, C.M., Charlet, K., Kiefer, F., Heinz, A., & Walter, H. (2022). Alcohol dependence decreases functional activation of the caudate nucleus during model‐based decision processes. Alcoholism: Clinical and Experimental Research, doi: http://doi.org/10.1111/acer.14812
• Marsh, J. E., Kattner, F., & Ruhnau, P. (2022). Research collection: On theoretical advancement in auditory distraction research. Auditory Perception & Cognition, 4(3-4), 133-138. doi: 10.1080/25742442.2022.2036524
• Matsushima, T., Miura, M., Patzke, N., Toji, N., Wada, K., Ogura, Y., Homma, K. J., Sgadò, P., & Vallortigara, G. (2022). Fetal blockade of nicotinic acetylcholine transmission causes autism-like impairment of biological motion preference in the neonatal chick. Cerebral Cortex Communications, tgac041, https://doi.org/10.1093/texcom/tgac041
• Meder, B., Mayrhofer, R., & Ruggeri, A. (2022). Developmental trajectories in the understanding of everyday uncertainty terms. Topics in Cognitive Science, 14, 258–281.
• Meder, B., Wu, C.M., Schulz, E., & Ruggeri, A. (2021). Development of directed and random exploration in children. Developmental Science, 24,(4), e13095.
• Nelson, J. D., Rosenauer, C., Crupi, V., Tentori, K. & Meder, B. (2022). The Likelihood Difference Heuristic and binary test selection given situation-specific utilities. Decision, 9(3), 285–319.
• Osman, M., Adams, Z., Meder, B., Bechlivanidis, C., Verduga, O., & Strong, C. (2022). People’s understanding of the concept of misinformation. Journal of Risk Research, 25(10), 1239–1258.
• Schad, D. J., & Rabovsky, M. (2022). Social distancing-induced deceleration can enhance subjective well-being. Applied psychology. Health and well-being, 10.1111/aphw.12414. Advance online publication. https://doi.org/10.1111/aphw.12414
• Schad, D.J. & Vasishth, S. (2022). The posterior probability of a null hypothesis given a statistically significant result. The Quantitative Methods for Psychology, doi: 10.48550/arXiv.1901.06889, Shiny app: https://danielschad.shinyapps.io/probnull
• Schad, D.J., Nicenboim, B., Bürkner, P.-C., Betancouort, M., & Vasishth, S. (2022). Workflow techniques for the robust use of Bayes factors. Psychological Methods, doi: 10.1037/met0000472, arXiv preprint: arXiv:2103.08744
• Swaboda, N., Meder, B., & Ruggeri, A. (2022). Finding the (most efficient) way out of a maze is easier than asking (good) questions. Developmental Psychology, 58(9), 1730–1746.
• Vasishth, S., Yadav, H., Schad, D.J., & Nicenboim, B. (2022). Sample size determination for Bayesian hierarchical models commonly used in psycholinguistics. Computational Brain and Behavior, doi: 10.1007/s42113-021-00125-y, PsyArXiv preprint: PsyArXiv:u8yvc
• Wu, C. M., Ho, M. K., Kahl, B., Leuker, C., Meder, B., & Kurvers, R. (2021). Specialization and selective social attention establishes the balance between individual and social learning. In Proceedings of the 43rd Annual Meeting of the Cognitive Science Society (pp. 1921–1927). Austin, TX: Cognitive Science Society.

    2021

• Meder, B., Crupi, V., & Nelson, J. D. (2021). What makes a good query? Prospects for a comprehensive theory of human information acquisition. In I. Cogliati-Dezza, E. Schulz, and C. M. Wu (Eds.). The drive for knowledge: the science of human information-seeking (pp. 101–123). Cambridge University Press.
• Meder, B., & Mayrhofer, R. (2021). Diagnostic causal reasoning. In M. Knauff and W. Spohn (Eds.), Handbook of rationality (pp. 449–460). MIT Press.
• Osman, M., McLachlan, S., Fenton, N., Neil, M., Löfstedt, R., & Meder, B. (2020). Learning from behavioural changes that fail. Trends in Cognitive Sciences, 24, 969–980.
• Stone, K., Verissimo, J, Schad, D.J., Oltrogge, E., Vasishth, S. & Lago, S. (2021). The interaction of grammatically distinct agreement dependencies in predictive processing. Language, Cognition and Neuroscience, 36(9), 1159-1179, doi: 10.1080/23273798.2021.1921816

• Universität Tübingen
• Universität zu Köln
• Martin-Luther Universität Halle-Wittenberg
• Technische Universität Darmstadt
• University of Central Lancashire
• Kyushu University
• University of Lincoln
• University of Wisconsin-Madison
• Medical School Hamburg
• Hokkaido University
• Justus-Liebig-Universität Giessen
• University of East London
• Charité Berlin
• Université de Genève
• Universiteit Utrecht
• Universität Leipzig
• Ruhr Universität Bochum
• Tilburg University
• Universität Koblenz Landau
• RWRH Aachen University
• Universität Stuttgart
• Technische Universität Dresden
• Universität Potsdam
• Max Planck UC Centre
• Max-Planck-Institut für Bildungsforschung
• Max-Planck-Institut für biologische Kybernetik
• University of Trento
• Georg-August-Universität Göttingen
• University of Cambridge
• University degli studi di Torino
• Universidade Federal do Rio de Janeiro