piwik-script

Intern
    Lehrstuhl für Psychologie I - Biologische Psychologie, Klinische Psychologie und Psychotherapie

    Publications

    Hilger, K., Häge, A., Zedler, C., Jost, M., & Pauli, P. (under Review). Pain-Related Fear in Virtual Reality: Differential Acquisition and Modification of Affective, Behavioral, and Physiological Components. (Preprint: https://doi.org/10.31234/osf.io/kgw8m)

    Thiele, J., Faskowitz, J., Sporns, O., & Hilger, K. (in revision). Multi-Task Brain Network Reconfiguration is Inversely Associated with General Intelligence. (Preprint: https://doi.org/10.1101/2021.07.31.454563)

    Hilger, K., & Hewig, J. (2021). Individual Differences in the Focus: Understanding Variations in Pain-Related Fear and Avoidance Behavior from the Perspective of Personality Science, PAIN, in press. http://doi.org/10.1097/j.pain.0000000000002359

    Glück, V. M.*, Engelke, P.*, Hilger, K.*, Wong, A. H. K., Boschet, J. M. & Pittig, A. (under Review). A network perspective on real-life threat: Complex associations between trait and situational anxiety, stress, and individual approach-avoidance tendencies. Preprint: https://psyarxiv.com/jnx36

    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.

    Hilger, K., & Sporns, O. (2021). Network Neuroscience Methods in Studying Intelligence. In A. K. Barbey, S. Kamara, & R. Haier (Eds.), The Cambridge Handbook of Intelligence and Cognitive Neuroscience. Cambridge University Press. https://doi.org/10.1017/9781108635462

    Hilger, K. & Markett, S. (2021). Personality network neuroscience: promises and challenges on the way towards a unifying framework of individual variability. Network Neuroscience, 5(2), 1-34. https://doi.org/10.1162/netn_a_00198

    Hilger, K., Sassenhagen, J., Kühnhausen, J., Reuter, M. Schwarz, U., Gawrilow, C, & Fiebach, C. J. (2020). Neurophysiological markers of ADHD symptoms in typically-developing children. Scientific Reports, 10, 22460. https://doi.org/10.1038/s41598-020-80562-0

    Hilger, K., Fukushima, M., Sporns, O., & Fiebach, C. J. (2020). Temporal stability of functional brain modules associated with human intelligence. Human brain mapping, 41(2), 362-372.

    Hilger, K., Winter, N., Leenings, R., Sassenhagen, J., Hahn, T., Basten, U., & Fiebach, C. J. (2020). Predicting Intelligence fron Brain Gray Matter Volume. Brain Structure and Function. https://doi.org/10.1007/s00429-020-02113-7

    Hilger, K., & Fiebach, C., J. (2019). ADHD Symptoms are Associated with the Modular Structure of Intrinsic Brain Networks in a Representative Sample of Healthy Adults. Network Neuroscience, 3(2), 567-588. https://doi.org/10.1162/netn_a_00083

    Hilger, K., Ekman, M., Fiebach, C. J., & Basten, U. (2017). Efficient hubs in the intelligent brain: Nodal efficiency of hub regions in the salience network is associated with general intelligence. Intelligence, 60, 10-25. http://doi.org/10.1016/j.intell.2016.11.001

    Galeano Weber, E., Hahn, T., Hilger, K., & Fiebach, C. J. (2017). Distributed patterns of occipito-parietal functional connectivity predict the precision and variability of visual working memory. NeuroImage, 146, 404-418.

    Hilger, K., Ekman, M., Fiebach, C. J., & Basten, U. (2017). Intelligence is associated with the modular structure of intrinsic brain networks. Scientific Reports, 7(1), 1–12. https://doi.org/10.1038/s41598-017-15795-7

    Basten, U., Hilger, K., & Fiebach, C. J. (2015). Where smart brains are different: A quantitative meta-analysis of functional and structural brain imaging studies on intelligence. Intelligence, 51, 10–27. http://doi.org/10.1016/j.intell.2015.04.009

    * geteilte Erstauthorenschaft