Publications

WORKING PAPER

Zhang, L., Gläscher, J. (in prep.). Falsifying cognitive computational models is as important as model selection: A tutorial on evaluating posterior predictions with hierarchical Bayesian methods.

Bayer, J., Rusch, T., Zhang, L., Gläscher, J., & Sommer, T. (under review). Dose-dependent effects of estrogen on prediction error related neural activity in the nucleus accumbens of healthy young women.

PREPRINTS

Zhang, L.*, Lengersdorff, L.*, Mikus, N., Gläscher, J., & Lamm, C. (2019). Using reinforcement learning models in social neuroscience: Frameworks, pitfalls, and suggestions. *Co-first authors. PsyArXiv, 10.31234/osf.io/uthw2

Zhang, L., Gläscher, J. (2019). A network supporting social influences in human decision-making. bioRxiv, 551614.

Crawley, D.*, Zhang, L.*, Emily, J., …, den Ouden, H., Loth, E., & the EU-AIMS LEAP group (2019). Modeling cognitive flexibility in autism spectrum disorder and typical development reveals comparable developmental shifts in learning mechanisms *Co-first authors. PsyArXiv, 10.31234/osf.io/h7jcm

Zhou, L.*, Zhang, L.*, Su, Y., & Liang, ZY. (2019). Is zero void? Attentional mechanism of hidden-zero effect in risky decision-making. *Co-first authors. PsyArXiv, 10.31234/osf.io/pmhsa

CONFERENCE PROCEEDINGS

Zhang, L., Kandil, F., Hilgetag, C.C., & Gläscher, J. (2019). The causal role of temporoparietal junction in computing social influence in human decision-making. Cognitive Computational Neuroscience (CCN 2019). Berlin, Germany. 10.32470/CCN.2019.1120-0

PEER-REVIEWED PUBLICATIONS

Zhou, L., Li. AM., Zhang, L., Li, S., & Liang, ZY. (2019). Similarity in processes of risky choice and intertemporal choice: The case of certainty effect and immediacy effect. Acta Psychologica Sinica. 51(3), 337-352.

Zhang, L., Redžepović, S., Rose, M., & Gläscher, J. (2018). Zen and the Art of Making a Bayesian Espresso. Neuron, 98(6), 1066-1068.

Hu, Y., He, L.*, Zhang, L.*, Wölk, T., Dreher, J. C., & Weber, B. (2018). Spreading inequality: Neural computations underlying paying-it-forward reciprocity. Social cognitive and affective neuroscience, 13(6), 578-589. *Equal contribution.

Ahn, W.-Y., Haines, N., & Zhang, L. (2017). Revealing neurocomputational mechanisms of reinforcement learning and decision-making with the hBayesDM package. Computational Psychiatry, 1, 24-57.

Yu, S., Lei. X., & Zhang, L. (2010). A survey on need-abandonment among university students. Proceedings of the 18th BNU “JingShi Cup” Academic Competition, the 3rd Prize, (in Chinese).

Zhang, L.*, Zheng, X.* (2009). An investigation of college students’ concept of death and self-identity attribution analysis. Proceedings of the 17th BNU “JingShi Cup” Academic Competition, the 2nd Prize, (in Chinese). *Co-first authors.

CONFERENCE ABSTRACTS

Zhang, L.*, Lengersdorff, L.*, Mikus, N., Gläscher, J., & Lamm, C. (2019). Using reinforcement learning models in social neuroscience: Frameworks, pitfalls, and suggestions. *Co-first authors. Talk presented at the 3rd Chinese Association for Psychological & Brain Science annual meeting. Utrecht, Netherlands.

Zhang, L., Kandil, F., Hilgetag, C.C., & Gläscher, J. (2019). The causal role of temporoparietal junction in computing social influence in human decision-making. Poster presented at Symposium on “Biology of Decision Making (SBDM). Oxford, UK.

Crawley, D.*, Zhang, L.*, Emily, J., …, den Ouden, H., Loth, E., & the EU-AIMS LEAP group (2019). Modeling cognitive flexibility in autism spectrum disorder and typical development reveals comparable developmental shifts in learning mechanisms. *Co-first authors. Poster to be presented at Roche Joint RPF/RiSE Symposium. Basel, Switzerland.

Zhang, L., Gläscher, J. (2018). Neurocomputational mechanisms of social influence in goal-directed learning. Poster (poster spotlight) presented at FENS Spring Brain Conference: Computational Neuroscience of Prediction. Rungstedgaard, Denmark.

Zhang, L., Hipp, J., Taylor, K., Chatham, C., & Bolognani, F. (2017). Age-binned normalization of VinelandTM-II increases variability in standard scores: Implications for clinical trials in Autism Spectrum Disorder (ASD). Poster presented at The International Meeting for Autism Research (IMFAR), San Francisco, CA, USA.

Haines, N., Zhang, L., & Ahn W.-Y. (2016). Revealing neuro-computational mechanisms of reinforcement learning and decision-making with the hBayesDM package. Poster to be presented at the Annual Meeting of the Society for Mathematical Psychology, New Brunswick, NJ, USA.

Zhou, L.*, Zhang, L.*, & Liang, Z.-Y. (2016). Comparing the underlying process between intertemporal choice and risky choice. Talk presented at the 35th Annual Meeting of the European Group of Process Tracing Studies (EGPROC), Bonn, Germany. *Co-first authors.

Zhang, L., Gläscher, J. (2015). Modeling social influence on human decision-making with reinforcement learning theory: A Bayesian perspective. Poster presented at the Society for Neuroscience Annual meeting (SfN 2015), Chicago, IL, USA.

Zhang, L., Gläscher, J. (2015). Modeling social influence on human decision-making. Talk presented at the 57th Conference of Experimental Psychologists (TeaP), Hildesheim, Germany.

Zhang, L., Gläscher, J. (2014). Reinforcement learning signals of social influence on human decision-making. Poster presented at the Bernstein Conference 2014, Göttingen, Germany.

Zhang, L., Martínez, A., & Salillas, E. (2014). The role of finger-based number representations in online arithmetic facts retrieval. Poster presented at the 20th Annual Meeting of the Organization for Human Brain Mapping (OHBM), Hamburg, Germany.

TALKS

Decision Neuroscience Lab (PI: Sebastian Gluth), University of Basel, Switzerland. 2019

Neuroeconomics Lab (PI: Jean-Claude Dreher), CNRS, Lyon, France. 2018

Loth Lab (PI: Eva Loth), King’s College London, London, UK. 2017

Roche NORD Research Forum, Basel, Switzerland. 2017

Internal seminar at UKE, Hamburg, Germany. 2016

International Workshop on the Neurobiology of Social Influence Moscow, Russia. 2015

BOOK TRANSLATIONS

Zheng, X., Zhang, L., & Jiang, W. (2016). Health psychology. China Light Industry Press. Beijing, China. [Original copy: Brannon, L., Feist, J., & Updegraff, J. (2013). Health psychology: An introduction to behavior and health. Cengage Learning. USA.]