Dr Lei Zhang BSc, MSc, PhD

Dr Lei Zhang

School of Psychology
Associate Professor
Director of Postgraduate Research

Contact details

Email
l.zhang.13@bham.ac.uk
Twitter
@lei_zhang_lz
View my research portal

Dr. Lei Zhang is a cognitive computational neuroscientist. He directs the Adaptive Learning Psychology and Neuroscience Lab, ALP(e)N Lab, which addresses the fundamental question of the “adaptive brain” by studying the cognitive, computational, and neurobiological basis of (social) learning and decision-making in health and disease (i.e. Computational Psychiatry).

Qualifications

  • PhD in Cognitive Neuroscience (summa cum laude), University of Hamburg & University Medical Center Hamburg-Eppendorf, Germany; Awarded Chinese Government Prize for Outstanding Doctoral Dissertation Abroad
  • MSc in Cognitive Neuroscience, University of the Basque Country & Basque Center on Cognition, Brain & Language, Spain
  • BSc in Psychology, Beijing Normal University, China

Biography

Dr Lei Zhang obtained his BSc in Psychology from Beijing Normal University, China, and his MSc in Cognitive Neuroscience at Basque Center on Cognition, Brain and Language, Spain. He received his PhD (summa cum laude), along with a one-year transition postdoc, with Dr Jan Gläscher at the Institute of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany. Between 2016 and 2017, he was a Roche intern for Scientific Exchange (RiSE) at one of the research-based pharmaceutical companies, F. Hoffmann-La Roche AG, based in Basel, Switzerland. Between 2019 and 2022, he worked as a postdoctoral fellow with Prof Claus Lamm at the Social Cognitive and Affective Neuroscience Unit (SCAN-Unit), University of Vienna, Austria. Dr Zhang joined the Centre for Human Brain Health, Institute of Mental Health, and School of Psychology at University of Birmingham as an Associate Professor in winter 2022.

Teaching

Dr Lei Zhang performs research-informed teaching. He teaches an MSc-level module on Proposing Research in Psychology.

Postgraduate supervision

PhD students: Students interested in working with Dr Zhang should email him to discuss potential funding opportunities. Current funding schemes include MRC-AIM, BBSRC-MIBTP, and CSC.

Postdoc researchers: Excellent and motivated postdoc researchers are welcome to contact Dr Zhang to discuss potential projects and funding opportunities (both national and international).

Research

Learning and decision-making, flexible & adaptive (learning) behavior, decision neuroscience/neuroeconomics, social learning, reinforcement learning, cognitive modeling, Bayesian methods, neuroimaging, fMRI, TMS, pain, aversive learning, computational psychiatry

Other activities

Awards

  • Rising Star Award, Association for Psychological Science (APS), 2022
  • Commendation Award for Open Science, European Society for Cognitive and Affective Neuroscience (ESCAN), 2022
  • Open & Reproducible Science Award, Society for Social Neuroscience (S4SN), 2021
  • Trainee Professional Development Award, Society for Neuroscience (SfN), 2020
  • Teaching Award for Early Career Researchers, University of Vienna, 2020
  • Fellow, Kavli Summer Institute in Cognitive Neuroscience (“Brain Camp”), Santa Barbara, CA, USA, 2019

Responsibilities

  • eLife Community Ambassador (2022-2024)
  • OHBM Student and Postdoc Special Interest Group (2021-2023)
  • S4SN Open Science Committee, Society for Social Neuroscience (2021–2022)
  • ALBA Network Member for diversity and equality in neurosciences (2021-present)
  • COS Ambassador, Center for Open Science (2020–present)
  • Steering committee member, Chinese Open Science Network (2018–present)

Publications

Highlight publications

Zhang, L & Gläscher, J 2020, 'A brain network supporting social influences in human decision-making', Science Advances. https://doi.org/10.1126/sciadv.abb4159

Crawley, D, Zhang, L, Jones, EJH, Ahmad, J, Oakley, B, San José Cáceres, A, Charman, T, Buitelaar, JK, Murphy, DGM, Chatham, C, den Ouden, H & Loth, E 2020, 'Modeling flexible behavior in childhood to adulthood shows age-dependent learning mechanisms and less optimal learning in autism in each age group', PLoS Biology, vol. 18, no. 10. https://doi.org/10.1371/journal.pbio.3000908

Zhang, L, Lengersdorff, L, Mikus, N, Gläscher, J & Lamm, C 2020, 'Using reinforcement learning models in social neuroscience: frameworks, pitfalls and suggestions of best practices', Social Cognitive and Affective Neuroscience, vol. 15, no. 6, pp. 695-707. https://doi.org/10.1093/scan/nsaa089

Zhao, Y, Zhang, L, Rütgen, M, Sladky, R & Lamm, C 2021, 'Neural dynamics between anterior insular cortex and right supramarginal gyrus dissociate genuine affect sharing from perceptual saliency of pretended pain', eLife, vol. 10, e69994. https://doi.org/10.7554/eLife.69994

Ahn, WY, Haines, N & Zhang, L 2017, 'Revealing neurocomputational mechanisms of reinforcement learning and decision-making with the hBayesDM package', Computational Psychiatry, vol. 1, pp. 24-57. https://doi.org/10.1162/CPSY_a_00002

Recent publications

Article

Pang, Y-X, Zhang, L, Yao, Y-W, Potenza, MN & Liu, L 2026, 'Altered uncertainty processing during adaptive learning in internet gaming disorder', Computers in Human Behavior, vol. 177, 108882. https://doi.org/10.1016/j.chb.2025.108882

Edwards, KL, Zhang, L, Flynn, AN, Karataş, KF, Lion, R, Zandstra, EH, Brunstrom, JM & Higgs, S 2026, 'Developing a novel computational model to quantify predictors of sustainable food choice', Food Quality and Preference, vol. 146, 106051. https://doi.org/10.1016/j.foodqual.2026.106051

Liang, Z-Y, Guo, M, Xu, Y, Liu, S-Y, Zhang, L & Zhou, L 2026, 'Does zero mean nothing? Investigating the attentional mechanism of the hidden-zero effect in risky decision-making', Psychonomic Bulletin and Review, vol. 33, no. 5, 157. https://doi.org/10.3758/s13423-026-02914-7

Zhang, R, Zhang, L, Hao, X-M, Dreher, J-C & Qu, C 2026, 'Learning to adaptively cooperate through social interactions during childhood and adolescence', npj Science of Learning, vol. 11, 32. https://doi.org/10.1038/s41539-026-00423-9

Wang, R, Luo, Y, Wang, Y, Zhang, L & Wu, H 2026, 'Towards naturalistic social neuroscience: A multi-level framework integrating real-world phenotyping, neurobiology, and computational mechanisms', Cognitive Affective & Behavioral Neuroscience. https://doi.org/10.3758/s13415-026-01413-5

Zhou, L, Li, L, Liang, Z, Li, S, Hui, Q & ZHANG, L 2026, '风险决策和跨期决策的过程比较: 基于概率和时间的等量转换范式', Acta Psychological Sinica, vol. 58, no. 6, pp. 1213-1236. https://doi.org/10.3724/SP.J.1041.2026.1213

Tomova, L, Towner, E, Thomas, K, Zhang, L, Palminteri, S & Blakemore, S-J 2025, 'Acute isolation is associated with increased reward seeking and reward learning in human adolescents', Communications Psychology, vol. 3, 135. https://doi.org/10.1038/s44271-025-00306-6

Massaccesi, C, Zhang, L, Silani, G & Lamm, C 2025, 'Avoiding Pain to Others Motivates Effortful Prosocial Behavior', Annals of the New York Academy of Sciences. https://doi.org/10.1111/nyas.70075

Xu, T, Zhang, L, Zhou, F, Fu, K, Gan, X, Chen, Z, Zhang, R, Lan, C, Wang, L, Kendrick, KM, Yao, D & Becker, B 2025, 'Distinct neural computations scale the violation of expected reward and emotion in social transgressions', Communications Biology, vol. 8, no. 1, 106. https://doi.org/10.1038/s42003-025-07561-7

Ong, JH, Zhang, L & Liu, F 2025, 'Do autistic individuals show atypical performance in probabilistic learning? A comparison of cue-number, predictive strength, and prediction error', Molecular Autism, vol. 16, no. 1, 15. https://doi.org/10.1186/s13229-025-00651-7

Pan, W, Geng, H, Zhang, L, Fengler, A, Frank, MJ, Zhang, R-Y & Chuan-Peng, H 2025, 'dockerHDDM: A user-friendly environment for Bayesian Hierarchical Drift-Diffusion Modeling', Advances in Methods and Practices in Psychological Science, vol. 8, no. 1, 25152459241298700. https://doi.org/10.1177/25152459241298700

Smith, E, Theis, H, van Eimeren, T, Knauth, K, Tuzsus, D, Zhang, L, Mathar, D & Peters, J 2025, 'Dopamine and Temporal Discounting: Revisiting Pharmacology and Individual Differences', The Journal of Neuroscience, vol. 45, no. 49, e0786252025. https://doi.org/10.1523/JNEUROSCI.0786-25.2025

Preprint

Suter, G, Antoniou, A, Zhang, L & Černis, E 2026 'Comparing non-clinical dissociative and psychotic-like experiences: reality monitoring and ‘fast thinking’ bias as possible cognitive correlates' OSF Preprints. <https://osf.io/preprints/psyarxiv/dt39r_v1>

Sohail, A & Zhang, L 2025 'BayesCog: A freely available course in Bayesian statistics and hierarchical Bayesian modeling for psychological science' PsyArXiv. https://doi.org/10.31234/osf.io/ua5ng_v1

Review article

Suter, G, Apperly, I, Zhang, L & Černis, E 2026, 'Reality monitoring across disorders of reality: Systematic and narrative reviews of dissociation and psychosis', Journal of Psychiatric Research, vol. 195, pp. 21-30. https://doi.org/10.1016/j.jpsychires.2026.01.021

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