Data Hub

We have established the TAM Data Hub for storing, mining and publishing data to make them findable, accessible, interoperable and reusable (FAIR). The Data Hub is particularly useful for understanding natural behavior, working on longitudinal questions, and combining data from healthy individuals and patients with mental disorders. It is a fundamental scientific tool for resolving the complexities of the human mind addressed in the five Key Areas. For more details see Public Outreach - Infrastructure.

Brand, O., Endres, D., Pfarr, J. K., Berger, C., Lenze, S., Fiehler, K., & Fleming, R. W. (2023). The Adaptive Mind Data and Code Policy.

New project-related publications
Arikan, B. E., van Kemenade, B. M., Fiehler, K., Kircher, T., Drewing, K., & Straube, B. (2021).
Different contributions of efferent and reafferent feedback to sensorimotor temporal recalibration.
Scientific Reports, 11(1).
Augustat, N., Chuang, L. C., Panitz, C., Stolz, C., Mueller, E. M., & Endres, D. M. (2022).
Modeling Reward Learning Under Placebo Expectancies: A Q-Learning Approach.
In Proceedings of the Annual Meeting of the Cognitive Science Society.
Borovska, P., de Haas, B. (2022).
Extrafoveal faces modulate the dynamics of scene viewing.
PsyArXiv Preprints
Broda, M. D., & de Haas, B. (2022).
Individual differences in looking at persons in scenes.
Journal of Vision, 22(12), 9-9.
Broda, M. D., & de Haas, B. (2022).
Individual fixation tendencies in person viewing generalize from images to videos.
i-Perception, 13(6), 20416695221128844.
Broda, M. D., & de Haas, B. (2023).
Reading the mind in the nose.
i-Perception, 14(3), 1–4.
Broda, M. D., Haddad, T., & de Haas, B. (2023).
Quick, eyes! Isolated upper face regions but not artificial features elicit rapid saccades.
Journal of Vision, 23(2), 5-5.
Broda, M.D., de Haas, B. (2022).
Reading the Mind in the Nose.
PsyArXiv Preprints
Eckert, A. L., Pabst, K., & Endres, D. M. (2022).
A Bayesian model for chronic pain.
Frontiers in Pain Research, 152.
Eckert, A. L., Pawlowski, J., Rief, W., Endres, D., & Kirchner, L. (2023).
Simulating Active Inference of Interpersonal Context Within and Across Mental Disorders.
PsyArXiv Preprints DOI DOI
Flachot, A., Akbarinia, A., Schütt, H. H., Fleming, R. W., Wichmann, F. A., & Gegenfurtner, K. R. (2022).
Deep neural models for color classification and color constancy.
Journal of vision, 22(4), 17-17.
Goktepe, N., & Schütz, A. C. (2023).
Familiar objects benefit more from transsaccadic feature predictions.
Attention, Perception, & Psychophysics, 1-13.
Goktepe, N., & Schütz, A. C. (2023).
Familiar objects benefit more from transsaccadic feature predictions.
Attention, Perception, & Psychophysics, 1-13.
Kadner, F., Thomas, T., Hoppe, D., & Rothkopf, C. A. (2023).
Improving saliency models' predictions of the next fixation with humans' intrinsic cost of gaze shifts.
In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (pp. 2104-2114).
Kavroulakis, E., van Kemenade, B. M., Arikan, B. E., Kircher, T., & Straube, B. (2022).
The effect of self- vs. externally generated actions on timing, duration and amplitude of BOLD response for visual feedback processing.
Human Brain Mapping, in press.
Kessler, F., Frankenstein, J., & Rothkopf, C. A. (2022).
A Dynamic Bayesian Actor Model explains Endpoint Variability in Homing Tasks.
Kirchner, L., Eckert, A., Berg, M., Endres, D., Straube, B., & Rief, W. (2022).
Better safe than sorry? - An active inference approach to biased inference on social contexts in depression.
PsyArXiv Preprints
Kollenda, D., de Haas, B. (2022).
The influence of familiarity on memory for faces and mask wearing.
Cognitive Research, 7(1).
Linka, M., Broda, M. D., Alsheimer, T. A., de Haas, B., & Ramon, M. (2022).
Characteristic fixation biases in Super-Recognizers.
Journal of Vision, in press.
Linka, M., Sensoy, Ö., Karimpur, H., Schwarzer, G., de Haas, B. (2022).
Attentional biases in free viewing of complex scenes in preschoolers and adults.
PsyArXiv Preprints
Linka, M., Sensoy, Ö., Karimpur, H., Schwarzer, G., de Haas, B. (2023).
Free viewing biases for complex scenes in preschoolers and adults.
Sci Rep, 13, 11803.
Lubinus, C., Einhäuser, W., Schiller, F., Kircher, T., Straube, B. & van Kemenade, B.M. (2022).
Action-based predictions affect visual perception, neural processing, and pupil size, regardless of temporal predictability.
NeuroImage, 263, 119601.
Meibodi, N., Abbasi, H., Schubö, A., & Endres, D. M. (2021).
A model of selection history in visual attention.
In Proceedings of the Annual Meeting of the Cognitive Science Society 43(43), 707-713.
Meibodi, N., Schubö, A., & Endres, D. (2022).
Sensorimotor processes are not a source of much noise: sensorimotor and decision components of reaction times.
In Proceedings of the Annual Meeting of the Cognitive Science Society.
Men, H., Altin, A., & Schütz, A. C. (2023).
Underestimation of the number of hidden objects.
Journal of Vision, 23(2):1, 1–20.
Niehaus, H.,Stroth, S., Kamp-Becker, I., Endres, D. (2022).
Modeling aberrant volatility estimates in Autism Spectrum Disorder.
In Proceedings of the Annual Meeting of the Cognitive Science Society.
Ody, E., Straube, B., He, Y., Kircher, T. (2023).
Perception of self-generated and externally-generated visual stimuli: Evidence from EEG and behavior.
Psychophysiology, e14295.
O’Leary, A., Fernàndez-Castillo, N., Gan, G., Yang, Y., Yotova, A. Y., Kranz, T. M., ... Kircher, T. …, Straube, B., ... Reif, A. (2022).
Behavioural and functional evidence revealing the role of RBFOX1 variation in multiple psychiatric disorders and traits.
Molecular Psychiatry, 1–10.
Pabst, K., Zittrell, F., Homberg, U., Endres, D. (2022).
A Model for Optic Flow Integration in Locust Central-Complex Neurons Tuned to Head Direction.
In Proceedings of the Annual Meeting of the Cognitive Science Society.
Ridderbusch, I. C., Wroblewski, A., Yang, Y., Richter, J., Hollandt, M. Hamm, A. O., Wittchen, H.-U., Ströhle, A., Arolt, V., Margraf, J., Lueken, U., Hermann, M. J., Kircher, T. & Straube, B. (2021).
Neural adaptation of cingulate and insular activity during delayed fear extinction: A replicable pattern across assessment sites and repeated measurements.
NeuroImage, 237, 118157.
Rothkopf, C., Bremmer, F., Fiehler, K., Dobs, K., & Triesch, J. (2023).
Models of vision need some action.
Behavioral Brain Science, 46:e405.
Schmitter, C.V., Kufer, K., Steinsträter, O., Sommer, J., Kircher, T., Straube, B. (2023).
Neural correlates of temporal recalibration to delayed auditory feedback of active and passive movements.
Human Brain Mapping.
Schramowski, P., Turan, C., Andersen, N., Rothkopf, C. A., & Kersting, K. (2022).
Large pre-trained language models contain human-like biases of what is right and wrong to do.
Nature Machine Intelligence, 4(3), 258-268.
Schultheis, M., Rothkopf. C. A., Koeppl, H. (2022).
Reinforcement learning with non-exponential discounting.
Neural Information Processing Systems.
Schultheis, M., Straub, D., & Rothkopf, C. A. (2021).
Inverse optimal control adapted to the noise characteristics of the human sensorimotor system.
Advances in Neural Information Processing Systems, 34, 9429-9442.
Straub, D., Schultheis, M., Koeppl, H., & Rothkopf, C. A. (2024).
Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs.
Advances in Neural Information Processing Systems, 36.
Straube, B., Kuehne, H., van Dam, L., Frey, K., van Kemenade, B.M., Kircher, T., & Ried, L. (2022).
Speech-gesture mismatch detection in individuals with high vs. low schizotypal traits.
International Consortium on Schizotypy Research, ICSR 2022.
Stroth, S., Niehaus, H., Wolff, N., Poustka, L., Roessner, V., Kamp‐Becker, I., & Endres, D. (2022).
Subdimensions of social‐communication behavior in autism—A replication study.
JCPP Advances, e12077.
Tatai, F., Straub, D., & Rothkopf, C. (2023).
People use Newtonian physics in intuitive sensorimotor decisions under risk. In
Proceedings of the Annual Meeting of the Cognitive Science Society (Vol. 45, No. 45).
Thomas, T., Straub, D., Tatai, F., Shene, M., Tosik, T., Kersting, K., & Rothkopf, C. A. (2024).
Modelling dataset bias in machine-learned theories of economic decision-making.
Nature Human Behaviour, 1-13.
Trick, S., & Rothkopf, C. A. (2022).
Bayesian Classifier Fusion with an Explicit Model of Correlation.
In International Conference on Artificial Intelligence and Statistics (pp. 2282-2310). PMLR.
Wagner, I., & Schütz, A. C. (2023).
Interaction of dynamic error signals in saccade adaptation.
Journal of Neurophysiology, 129, 717-723.
Wroblewski, A., Hollandt, M., Yang, Y., Ridderbusch, I.C., Pietzner, A., Szeska, C., Lotze, M., Wittchen, H.-U., Heinig, I., Pittig, A., Arolt, V., Koelkebeck, K., Rothkopf, C.A., Adolph, D., Margraf, J., Lueken, U., Pauli, P., Herrmann, M.J., Winkler, M.H., Ströhle, A., Dannlowski, U., Kircher, T., Hamm, A.O., Straube, B.* & Richter, J.* (2022). *contributed equally
Sometimes I feel the fear of uncertainty stinging clear: How Intolerance of Uncertainty and Trait Anxiety impact fear acquisition, extinction and the return of fear.
PsyArXiv Preprints
Zečević, M., Dhami, D. S., Rothkopf, C. A., & Kersting, K. (2021).
Structural Causal Interpretation Theorem.
arXiv preprint