García Alanis, J. C., Strelow, A. E., Dort, M., Christiansen, H., Pinquart, M., & Panitz, C. (2022). Expectation violations, expectation change, and expectation persistence: The scientific landscape as revealed by bibliometric network analyses. PsyArXiv.

Sadus, K., Göttmann, J., & Schubert, A.-L. (2021). Predictors of stockpiling behavior during the COVID-19 pandemic in Germany. PsyArXiv.

Schubert, A.-L., Löffler, C., Hein, J., Schröer, P., Teuber, A., Sadus, K., & Hagemann, D. (2020). Tic Toc: How working memory load affects intelligence test performance under different time constraints. PsyArXiv.

in press

Frischkorn, G. T., Hilger, K., Kretzschmar, A., & Schubert, A.-L. (in press). Intelligenzdiagnostik der Zukunft: Ein Plädoyer für eine prozessorientierte und biologisch inspirierte Intelligenzmessung. Psychologische Rundschau.

Schubert, A.-L., Löffler, C., & Hagemann, D. (in press). A Neurocognitive Psychometrics Account of Individual Differences in Attentional Control. Journal of Experimental Psychology: General.


Löffler, C., Frischkorn, G. T., Rummel, J., Hagemann, D., & Schubert, A.-L. (2022). Do attentional lapses account for the worst performance rule? Journal of Intelligence,10(1), 2.
    Mirman, D., Scheel, A. M., Schubert, A.-L., & McIntosh, R. D. (2022). Strengthening derivation chains in cognitive neuroscience: A special issue of Cortex. Cortex, 146, A1–A4.


    Euler, M. J., & Schubert, A.-L. (2021). Recent developments, current challenges, and future directions in electrophysiological approaches to studying intelligence. Intelligence, 88, 101569.
      Jungeblut, H. M., Hagemann, D., Löffler, C., & Schubert, A.-L. (2021). An Investigation of the Slope Parameters of Reaction Times and P3 Latencies in the Sternberg Memory Scanning Task – A Fixed-Links Model Approach. Journal of Cognition, 4(1), 26.

        Rummel, J., Hagemann, D., Steindorf, L., & Schubert, A.-L. (2021). How consistent is mind wandering across situations and tasks?—A latent state–trait analysis. Journal of Experimental Psychology: Learning, Memory, and Cognition. Advance online publication.

        Schubert, A.-L., Ferreira, M. B., Mata, A., & Riemenschneider, B. (2021). A diffusion model analysis of belief bias: Different cognitive mechanisms explain how cognitive abilities and thinking styles contribute to conflict resolution in reasoning. Cognition, 211, 104629.

        Schubert, A.-L., Hagemann, D., & Göttmann, J. (2021). Do individual effects reflect quantitative or qualitative differences in cognition? Journal of Cognition, 4(1), 50.

        Schubert, A.-L., Hagemann, D., Löffler, C., Rummel, J., & Arnau, S. (2021). A chronometric model of the relationship between frontal midline theta functional connectivity and human intelligence. Journal of Experimental Psychology. General, 150(1), 1–22.


        Arnau, S., Löffler, C., Rummel, J., Hagemann, D., Wascher, E., & Schubert, A.-L. (2020). Inter-trial alpha power indicates mind wandering. Psychophysiology, 57(6), e13581.
          Klatt, L.-I., Schneider, D., Schubert, A.-L., Hanenberg, C., Lewald, J., Wascher, E., & Getzmann, S. (2020).
          Unraveling the relation between eeg correlates of attentional orienting and sound localization performance: A diffusion model approach. Journal of Cognitive Neuroscience, 32(5), 945–962.
            Lerche, V., von Krause, M., Voss, A., Frischkorn, G. T., Schubert, A.-L., & Hagemann, D. (2020). Diffusion modeling and intelligence: Drift rates show both domain-general and domain-specific relations with intelligence. Journal of Experimental Psychology. General, 149(12), 2207–2249.
              Schubert, A.-L., & Frischkorn, G. T. (2020). Neurocognitive psychometrics of intelligence: How measurement advancements unveiled the role of mental speed in intelligence differences: Current Directions in Psychological Science, 29(2), 140–146.
                Schubert, A.-L., Frischkorn, G. T., & Rummel, J. (2020). The validity of the online thought-probing procedure of mind wandering is not threatened by variations of probe rate and probe framing. Psychological Research, 84(7), 1846–1856.
                  Schubert, A.-L., Hagemann, D., Löffler, C., & Frischkorn, G. T. (2020). Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence. Journal of Intelligence, 8(1), 1.
                    von Krause, M., Lerche, V., Schubert, A.-L., & Voss, A. (2020). Do Non-Decision Times Mediate the Association between Age and Intelligence across Different Content and Process Domains? Journal of Intelligence, 8(3), 33.


                    Frischkorn, G. T., Schubert, A.-L., & Hagemann, D. (2019). Processing speed, working memory, and executive functions: Independent or inter-related predictors of general intelligence. Intelligence, 75, 95–110.
                      Schubert, A.-L. (2019). A meta-analysis of the worst performance rule. Intelligence, 73, 88–100.
                        Schubert, A.-L., Nunez, M. D., Hagemann, D., & Vandekerckhove, J. (2019). Individual differences in cortical processing speed predict cognitive abilities: A model-based cognitive neuroscience account. Computational Brain & Behavior, 2(2), 64–84.
                          Schubert, A.-L., & Rey-Mermet, A. (2019). Does process overlap theory replace the issues of general intelligence with the issues of attentional control? Journal of Applied Research in Memory and Cognition, 8(3), 277–283.


                          Frischkorn, G. T., & Schubert, A.-L. (2018). Cognitive models in intelligence research: Advantages and recommendations for their application. Journal of Intelligence, 6(3), 34.
                            Klotz, A.-L., Tauber, B., Schubert, A.-L., Hassel, A. J., Schröder, J., Wahl, H.-W., Rammelsberg, P., & Zenthöfer, A. (2018). Oral health-related quality of life as a predictor of subjective well-being among older adults—A decade-long longitudinal cohort study. Community Dentistry and Oral Epidemiology, 46(6), 631–638.
                              Schubert, A.-L., Hagemann, D., Frischkorn, G. T., & Herpertz, S. C. (2018). Faster, but not smarter: An experimental analysis of the relationship between mental speed and mental abilities. Intelligence, 71, 66–75.
                                Zähringer, J., Falquez, R., Schubert, A.-L., Nees, F., & Barnow, S. (2018). Neural correlates of reappraisal considering working memory capacity and cognitive flexibility. Brain Imaging and Behavior, 12(6), 1529–1543.


                                Schubert, A.-L., Hagemann, D., & Frischkorn, G. T. (2017). Is general intelligence little more than the speed of higher-order processing? Journal of Experimental Psychology. General, 146(10), 1498–1512.

                                  Schubert, A.-L., Hagemann, D., Voss, A., & Bergmann, K. (2017). Evaluating the model fit of diffusion models with the root mean square error of approximation. Journal of Mathematical Psychology, 77, 29–45.


                                  Bergmann, K., Schubert, A.-L., Hagemann, D., & Schankin, A. (2016). Age-related differences in the P3 amplitude in change blindness. Psychological Research, 80(4), 660–676.

                                    Schankin, A., Bergmann, K., Schubert, A.-L., & Hagemann, D. (2016). The allocation of attention in change detection and change blindness. Journal of Psychophysiology, 31(3), 94–106.

                                      Schubert, A.-L., Frischkorn, G. T., Hagemann, D., & Voss, A. (2016). Trait characteristics of diffusion model parameters. Journal of Intelligence, 4(3), 7.

                                        Schubert, A.-L., Hagemann, D., Voss, A., Schankin, A., & Bergmann, K. (2015). Decomposing the relationship between mental speed and mental abilities. Intelligence, 51, 28–46.


                                        Mata, A., Schubert, A.-L., & B. Ferreira, M. (2014). The role of language comprehension in reasoning: How “good-enough” representations induce biases. Cognition, 133(2), 457–463.